Worldwide Prevalence of Anaemia 1993–2005 WHO Global Database on Anaemia

Worldwide prevalence of anaemia 1993–2005 WHO Global Database on Anaemia

Centers for Disease Control and Prevention Atlanta

Worldwide prevalence of anaemia 1993–2005 WHO Global Database on Anaemia

Editors Bruno de Benoist World Health Organization Geneva, Switzerland Erin McLean World Health Organization Geneva, Switzerland Ines Egli Institute of Food Science and Nutrition, ETH – Zurich, Switzerland Mary Cogswell Centers for Disease Control and Prevention Atlanta, Georgia WHO Library Cataloguing-in-Publication Data Worldwide prevalence of anaemia 1993–2005 : WHO global database on anaemia / Edited by Bruno de Benoist, Erin McLean, Ines Egli and Mary Cogswell. 1.Anemia – prevention and control. 2.Anemia – epidemiology. 3.Prevalence. I.World Health Organization. ISBN 978 92 4 159665 7 (NLM classification: WH 155)

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Preface v Acknowledgements vi Abbreviations vii 1. Introduction 1 1.1 Anaemia: a public health problem 1 1.1.1 Etiology 1 1.1.2 Health consequences 1 1.1.3 Assessing anaemia 1 1.2 Control of anaemia 1 1.2.1 Correcting anaemia 1 2. Methods 3 2.1 Data sources – The WHO Global Database on Anaemia 3 2.2 Selection of survey data 3 2.2.1 Administrative level 3 2.2.2 Population groups 4 2.3 Defining anaemia 4 2.3.1 Haemoglobin threshold 4 2.3.2 Estimated anaemia prevalence for countries with no survey data 5 2.3.3 Uncertainty of estimates 5 2.3.4 Combining national estimates 5 2.3.5 Global anaemia prevalence 5 2.3.6 Classification of anaemia as a problem of public health significance 6 2.4 Population coverage, proportion of population, and the number of individuals with anaemia 6 2.4.1 Population coverage 6 2.4.2 Proportion of population and the number of individuals affected 6 3. Results and Discussion 7 3.1 Results 7 3.1.1. Population coverage 7 3.1.2 Proportion of population and number of individuals with anaemia 7 3.1.3 Classification of countries by degree of public health significance of anaemia 8 3.2 Discussion 8 3.2.1 Population coverage 8 3.2.2 Strengths of estimates 8 3.2.3 Limitations of estimates 8 3.2.4 Proportion of population and the number of individuals with anaemia 12 3.2.5 Classification of countries by degree of public health significance of anaemia, based on haemoglobin concentration 12 3.2.6 Comparison to previous estimates 12 3.3 Conclusion 12 References 14

Contents iii Annexes Annex 1 WHO Member States grouped by WHO and UN regions 15 Table A1.1 WHO Member States grouped by WHO regions 15 Table A1.2 WHO Member States grouped by UN regions and subregions 16 Annex 2 Results by UN region 18 Table A2.1 Population coverage by anaemia prevalence surveys (national or subnational) conducted between 1993 and 2005 by UN region 18 Table A2.2 Anaemia prevalence by UN region 18 Annex 3 National estimates of anaemia 20 Table A3.1 Country estimates of anaemia prevalence in preschool-age children 20 Table A3.2 Country estimates of anaemia prevalence in pregnant women 25 Table A3.3 Country estimates of anaemia prevalence in non-pregnant women of reproductive age 30 Table A3.4 Country references 35 Tables Table 2.1 Haemoglobin thresholds used to define anaemia 4 Table 2.2 Prediction equations used to generate anaemia estimates for countries without survey data 5 Table 2.3 Classification of anaemia as a problem of public health significance 6 Table 3.1 Population coverage (%) by anaemia prevalence surveys (national or subnational) conducted between 1993 and 2005 7 Table 3.2 Global anaemia prevalence and number of individuals affected 7 Table 3.3 Anaemia prevalence and number of individuals affected in preschool-age children, non-pregnant women and pregnant women in each WHO region 8 Table 3.4 Number of countries categorized by public health significance of anaemia 8 Figures Figure 3.1 Anaemia as a public health problem by country (a) Preschool-age children 9 (b) Pregnant women 10 (c) Non-pregnant women of reproductive age 11

iv worldwide prevalence of anaemia 1993–2005 Preface

Anaemia is a public health problem that affects populations The data available for school-age children, men, and the in both rich and poor countries. Although the primary elderly were not sufficient to generate regional or country- cause is iron deficiency, it is seldom present in isolation. level estimates for these groups, and therefore only global More frequently it coexists with a number of other causes, estimates for these groups are presented. such as malaria, parasitic infection, nutritional deficiencies, In addition, despite the fact that iron deficiency is con- and haemoglobinopathies. sidered to be the primary cause of anaemia, there are few Given the importance of this pathology in the world, nu- data on the prevalence of this deficiency. The likely reason merous countries conduct interventions to reduce anaemia; is that iron assessment is difficult because the available in- particularly in the groups most susceptible to its devastat- dicators of iron status do not provide sufficient information ing effects: pregnant women and young children. In order alone and must be used in combination to obtain reliable to assess the impact of these interventions, the adequacy information on the existence of iron deficiency. Further- of the strategies implemented, and the progress made in more, there is no real consensus on the best combination of the fight against anaemia, information on anaemia preva- indicators to use. Another reason is that the role of factors lence must be collected. This is the primary objective of the other than iron deficiency in the development of anaemia WHO Global Database on Anaemia. However, estimates has been underestimated by public health officials, because of anaemia prevalence by themselves are only useful if they for a long time anaemia has been confused with iron defi- are associated with a picture of the various causal factors ciency anaemia, and this has influenced the development of that contribute to the development of anaemia in specific strategies and programmes designed to control anaemia. settings. Indeed these factors are multiple and complex, and In this report, the prevalence of anaemia is presented by it is critical to collect accurate information about them to country and by WHO regions. Because these prevalence provide the basis for developing the best interventions for data may be used to identify programme needs by other anaemia control. United Nations agencies, we have presented the estimates In the last three decades, there have been various at- classified by United Nations regions in the annexes. In ad- tempts to produce estimates of the prevalence of anaemia dition, one chapter is dedicated to the criteria used to iden- at different levels including at the global level, but until tify, revise, and select the surveys, and the methodology the present time, there has never been a systematic review developed to generate national, regional, and global esti- of all of the data collected and published with the objec- mates. tive of deriving regional and global estimates. The WHO A lesson learned from producing this report is that in Global Database on Anaemia has filled this gap: data from order for the database to reach its full potential, data should 93 countries, representing as much as 76% of the popula- be collected on other vulnerable population groups such as tion in the case of preschool-age children, were analysed the elderly and school-age children, and surveys should be and used to develop statistical models to generate national more inclusive and collect information on iron status and prevalence estimates for countries with no data within the other causes of anaemia. time frame specified. This report is written for public health officials, nutri- It is surprising that given the public health importance tionists, and researchers. We hope that readers find it useful of anaemia, there are numerous countries lacking national and feel free to share any comments with us. prevalence data. Moreover, most survey data are related to the three population groups: preschool-age children, Bruno de Benoist pregnant women, and non-pregnant women of reproduc- Coordinator, Micronutrient Unit tive age, which is why the report focuses on these groups. World Health Organization

Preface v Acknowledgements

The WHO Global Database on Anaemia was developed by WHO wishes to thank the numerous individuals, insti- the Micronutrient team in the Department of Nutrition for tutions, governments, non-governmental, and international Health and Development with the financial support of the organizations for providing data for the database. Without Centers for Disease Control and Prevention. continual international collaboration in keeping the data- The estimates for the database were produced by Erin base up-to-date, this compilation on the global situation McLean, Mary Cogswell, Ines Egli, and Daniel Wojdyla and trends in anaemia prevalence would not have been pos- with contributions from Trudy Wijnhoven, Laurence sible. Special thanks are due to ministries of health of the Grummer-Strawn, and Bradley Woodruff, under the co- WHO Member States, WHO regional offices, and WHO ordination of Bruno de Benoist. Grace Rob and Ann-Beth country offices. Moller assisted in data management.

vi worldwide prevalence of anaemia 1993–2005 Abbreviations

CDC Centers for Disease Control and Prevention Hb Haemoglobin HDI Human Development Index: a composite indicator of wealth, life expectancy and education developed by the United Nations Development Programme. IDA Iron deficiency anaemia NHANES National Health and Nutrition Examination Survey NPW Non-pregnant women (15.00–49.99 yrs) PreSAC Preschool-age children (0.00–4.99 yrs) PW Pregnant women SD Standard deviation UN United Nations VMNIS Vitamin and mineral nutrition information system WHO World Health Organization CRP C-reactive protein

Abbreviations vii

1. Introduction

1.1 Anaemia: a public health problem the negative consequences of IDA on cognitive and physi- Anaemia is a global public health problem affecting both cal development of children, and on physical performance developing and developed countries with major conse- – particularly work productivity in adults – are of major quences for human health as well as social and economic concern (2). development. It occurs at all stages of the life cycle, but is more prevalent in pregnant women and young children. 1.1.3 Assessing anaemia In 2002, iron deficiency anaemia (IDA) was considered to Hb concentration is the most reliable indicator of anae- be among the most important contributing factors to the mia at the population level, as opposed to clinical meas- global burden of disease (1). ures which are subjective and therefore have more room for error. Measuring Hb concentration is relatively easy and 1.1.1 Etiology inexpensive, and this measurement is frequently used as a Anaemia is the result of a wide variety of causes that can be proxy indicator of iron deficiency. However, anaemia can isolated, but more often coexist. Globally, the most signifi- be caused by factors other than iron deficiency. In addition, cant contributor to the onset of anaemia is iron deficiency in populations where the prevalence of inherited haemo- so that IDA and anaemia are often used synonymously, and globinopathies is high, the mean level of Hb concentration the prevalence of anaemia has often been used as a proxy may be lowered. This underlines that the etiology of anae- for IDA. It is generally assumed that 50% of the cases of mia should be interpreted with caution if the only indicator anaemia are due to iron deficiency 2( ), but the proportion used is Hb concentration. The main objective for assess- may vary among population groups and in different areas ing anaemia is to inform decision-makers on the type of according to the local conditions. The main risk factors for measures to be taken to prevent and control anaemia. This IDA include a low intake of iron, poor absorption of iron implies that in addition to the measurement of Hb concen- from diets high in phytate or phenolic compounds, and pe- tration, the causes of anaemia need to be identified consid- riod of life when iron requirements are especially high (i.e. ering that they may vary according to the population. growth and pregnancy). Among the other causes of anaemia, heavy blood loss as 1.2 Control of anaemia a result of menstruation, or parasite infections such as hook- 1.2.1 Correcting anaemia worms, ascaris, and schistosomiasis can lower blood haemo- Given the multifactorial nature of this disease, correcting globin (Hb) concentrations. Acute and chronic infections, anaemia often requires an integrated approach. In order including malaria, cancer, tuberculosis, and HIV can also to effectively combat it, the contributing factors must be lower blood Hb concentrations. The presence of other micro- identified and addressed. In settings where iron deficiency nutrient deficiencies, including vitamins A and B12, folate, is the most frequent cause, additional iron intake is usually riboflavin, and copper can increase the risk of anaemia. Fur- provided through iron supplements to vulnerable groups; thermore, the impact of haemoglobinopathies on anaemia in particular pregnant women and young children. Food- prevalence needs to be considered within some populations. based approaches to increase iron intake through food fortification and dietary diversification are important, sus- 1.1.2 Health consequences tainable strategies for preventing IDA in the general pop- Anaemia is an indicator of both poor nutrition and poor ulation. In settings where iron deficiency is not the only health. The most dramatic health effects of anaemia, i.e., cause of anaemia, approaches that combine iron interven- increased risk of maternal and child mortality due to severe tions with other measures are needed. anaemia, have been well documented (3–5). In addition, Strategies should include addressing other causes of

1. Introduction 1 anaemia (6,7),1.2 and should be built into the primary health care system and existing programmes. These strategies should be tailored to local conditions, taking into account the specific etiology and prevalence of anaemia in a given setting and population group.

1 http://www.who.int/malaria/docs/TreatmentGuidelines2006.pdf 2 http://www.who.int/wormcontrol/documents/en/Controlling%20 Helminths.pdf

2 worldwide prevalence of anaemia 1993–2005 2. Methods

2.1 Data sources – The WHO Global Database country using two variables: the administrative level for on Anaemia which the survey was representative, and the population The estimates presented are based on data from the WHO group surveyed. Global Database on Anaemia; a part of the Vitamin and Mineral Nutrition Information System (VMNIS), main- 2.2.1 Administrative level tained at WHO. Surveys were selected based on the administrative level Data are collected from the scientific literature and they represented. Surveys were classified as national when through collaborators, including WHO regional and they were based on a nationally representative sample. Sub country offices, United Nations organizations, ministries national surveys were also available in the database and of health, research and academic institutions, and non- were classified according to the population that they rep- governmental organizations. MEDLINE and WHO re- resented as regional (multiple states), state (representative gional databases were searched systematically, and manual of the first administrative level boundary), district (repre- searches were conducted to find articles published in non- sentative of the second administrative level boundary), or indexed medical and professional journals. For inclusion in local surveys. the database, Hb must be measured in capillary, venous, Data from the most recent national survey was used in or cord blood using quantitative photometric methods or preference to subnational surveys. For one country, where automated cell counters. In addition, anaemia prevalence or an area had been left out of a national survey because of mean Hb concentrations have to be reported. Surveys were security concerns, available data from the missing region excluded if they measured only clinical signs of anaemia or was pooled with the national data and weighted by the gen- haematocrit. Data are included in the database if they are eral population estimate for that area to provide a national representative of any administrative level within a country, estimate for that country. This proportion was determined including nationally representative data and surveys repre- by using the most recent census data from the country. If sentative of a region, the first administrative level bound- two national surveys were conducted in the same year, sur- ary, second administrative level boundary or local surveys. vey results were pooled into a single summary measure and As of December 31, 2005, 696 surveys were available in the weighted by the survey sample size. database; the majority of these in women or preschool-age In the absence of national data, surveys representative of children. at least the first administrative level boundary were used if two or more surveys at this level were available for the pop- 2.2 Selection of survey data ulation group and country concerned within the accept- The time frame for the current estimates is 1993–2005 and able time frame. Results were pooled into a single summary survey data for WHO’s 1921 Member States were extracted measure, weighted by the total general population for that from the database. Data on anaemia were selected for each region or state, and based on the most recent and available census data between 1993 and 2005. Local- and district- level surveys were not used in these estimates since they 1 On 3 June 2006, the Permanent Representative of the Republic of Serbia have the potential for more bias. to the United Nations and other International Organizations in Geneva informed the Acting Director-General of the WHO that “the member- Surveys with prevalence data based on a sample size of ship of the state union Serbia and Montenegro in the United Nations, less than 100 subjects were excluded in most cases. This including all organs and the organizations of the United Nations sys- was done because with a sample size of 100 and a confi- tem, is continued by the Republic of Serbia on the basis of Article 60 of the Constitutional Charter of Serbia and Montenegro, activated by the dence level of 95%, the error around an estimate of anae- Declaration of Independence adopted by the National Assembly of Mon- mia prevalence of 50% would be +/-10 percentage points. A tenegro on 3 June 2006”. Estimates used or referred to in this document cover a period of time preceding that communication. smaller sample size would have an even larger error. How-

2. Methods 3 ever, a few exceptions were made. National surveys with and altitude (10), and therefore the prevalence of anaemia fewer than 100 subjects but more than 50 subjects were corrected for these factors was used when provided by the only accepted where the results were being extrapolated to survey. No other corrections were accepted. fewer than 500,000 people; or to pregnant women, since Some surveys did not present data using the WHO Hb the numbers in this group are frequently small, especially in thresholds to define anaemia. When this occurred, preva- populations with a lower rate of reproduction. lence was estimated by assuming that the Hb concentration was normally distributed within the population and esti- 2.2.2 Population groups mating anaemia prevalence by using one of the following Population groups are as follows: preschool-age children methods in order of preference: (0–4.99 yrs), school-age children (5.00–14.99 yrs), preg- 1. The mean and standard deviation (SD) of the Hb con- nant women (no age range defined), non-pregnant women centration were used to estimate the proportion of in- (15.00–49.99 yrs), men (15.00–59.99 yrs), and elderly (both dividuals falling below the appropriate Hb cut-off for sexes >60 yrs). Wherever possible, children below 0.5 yrs the population group (n=20 surveys). The correlation were excluded from the estimate for preschool-age children between the estimated and predicted prevalence of anae- since the cut-off for anaemia is not defined in this age group. mia was determined using surveys from the database However, the estimate was applied to the entire popula- where a mean, an SD, and a prevalence for the WHO tion of children less than 5 yrs of age. Occasionally, in the age- and sex-specific cut-off were provided. The relation- non-pregnant women group, pregnant women could not be ship was plotted (n=508 surveys), and for most surveys, excluded because all women were included in the figure pro- the two figures were extremely close (r2≥0.95, p<0.001) vided in the country report; but pregnant women were often for all four Hb thresholds (110, 115, 120, 130 g/l). On a small proportion of the group and their exclusion would average, the predicted prevalence overestimated actual not be expected to change the figure significantly. If a sur- prevalence by 3.8 percentage points. For 6.5% of the vey reported results by physiological status, lactating women surveys in the analysis, actual anaemia prevalence was were combined with non-pregnant non-lactating women to overestimated by 10 percentage points or more. provide the estimate for non-pregnant women. Data disaggregated by age closest to the defined age 2. When no SD was provided, but the prevalence for a non- range for the population groups were used. If the age range WHO cut-off and mean Hb concentrations were avail- overlapped two population groups, the survey was placed able (n=3 surveys), we used these two figures to calculate with the group with the greatest overlap in age. When the the SD of the Hb concentration by assuming a normal age range was unavailable, the mean age of the sample was distribution within the population and deriving the Z used to classify the data. If this was unavailable or if the age score in order to back calculate the SD [SD= (Provided range equally spanned two population groups, the popula- cut-off – Mean Hb)/ Z score for proportion]. Following tion-specific Hb concentration threshold was used to clas- this calculation, the mean and SD were used as above to sify the data. If data represented less than 20% of the age derive the prevalence for the WHO cut-off. range of a population group, the survey was excluded. 3. For surveys (n=23) that did not present the mean and 2.3 Defining anaemia SD, nor the prevalence at the recommended threshold, the prevalence of anaemia was estimated from the preva- 2.3.1 Haemoglobin threshold lence at an alternative threshold. An average SD for the Normal Hb distributions vary with age, sex, and physiolog- same population group was assumed to be similar to ical status, e.g., during pregnancy (8). WHO Hb thresh- the actual SD in the survey. The mean SD of the Hb olds were used to classify individuals living at sea level as concentration for each population group was calculated anaemic (Table 2.1) (2). Statistical and physiological evi- from surveys included in the estimates, which had data dence indicate that Hb distributions vary with smoking (9) available for subjects within the defined age range of the population group (preschool-age children, SD=13.8 g/l; Table 2.1 Haemoglobin thresholds used to define anaemia school-age children, 11.3 g/l; non-pregnant women, 13.7 Age or gender group Haemoglobin threshold (g/l) g/l; pregnant women, 14.0 g/l; and men, 14.5 g/l). The Children (0.50–4.99 yrs) 110 population mean Hb concentration was estimated from Children (5.00–11.99 yrs) 115 the prevalence at the cut-off provided in the survey and Children (12.00–14.99 yrs) 120 the assumed SD. Non-pregnant women (≥15.00 yrs) 120 Pregnant women 110 Sometimes it was necessary to make adjustments for ag- Men (≥15.00 yrs) 130 gregated or disaggregated data. For example, one estimate Source: adapted from reference (2) was sometimes provided for school-age children utilizing 1)

4 worldwide prevalence of anaemia 1993–2005

1 The time frame for these estimates precedes the cession of Serbia and Montenegro, and therefore estimates in this report are presented for 192 member states as they were in 2005. one non-WHO cut-off for anaemia where two should have Anaemia prevalence was estimated by using the predic- been used; or 2) using two non-WHO cut-offs. In the first tion equations (Table 2.2) in countries where only explana- case, the prevalence was adjusted for the WHO cut-off that tory variables were known. For one country, none of the applied to the group in the majority. In the second case, covariates were available and therefore, a country-level esti- the prevalence was adjusted by assuming that the cut-off mate was not generated. applied to the group in the majority had been used for the entire group. 2.3.3 Uncertainty of estimates Data provided for separate groups frequently had to be For estimates based on survey data, each estimate was con- combined, such as data for women by physiological status sidered to be representative of the entire country whether or any other population group disaggregated by age. Prev- from a national or subnational sample, and the variance was alence estimates were combined and weighted by sample calculated in the logit scale using the sample size. A design size, and where this information was unavailable for one effect of 2 was applied since most surveys utilized cluster of the groups, it was assumed to have the average number sampling. From the prevalence, the variance and the de- of subjects of the other groups. If sample size information sign effect, a 95% confidence interval was generated in logit was missing from all data pooled, equal weight was given scale and then transformed to the original scale (17,18). to each survey. For regression-based estimates, a point estimate and 95% prediction interval were computed by using the logit 2.3.2 Estimated anaemia prevalence for countries with transformations in the regression models (19) and then no survey data back-transforming them to the original scale (20). Some countries did not have any survey data that met the criteria for the estimates. Therefore, a regression model was 2.3.4 Combining national estimates developed using countries with anaemia prevalence data Country estimates were combined to provide estimates at and the 2002 United Nations Human Development Index the global level as well as by WHO region for women and (HDI) (11) – which is a composite indicator of a life expect- preschool-age children by pooling the data and weighting ancy index, an education index, and a wealth index (12) it by the population that each estimate represented. Ninety- – and health indicators from the World Health Statistics five percent confidence intervals were constructed using the Database (13), so that anaemia prevalence could be pre- estimated variance of the weighted average. For one coun- dicted for the countries without data. try without data, no proxy indicators were available and so Separate prediction equations for each population group no country estimate was generated, but the UN subregional were based on countries with anaemia prevalence data for estimate had to be applied to that country to make regional that group. Seventeen countries did not have an HDI, and and global estimates. so HDI was estimated using two of the components and a proxy indicator for education (average years of schooling 2.3.5 Global anaemia prevalence in adults) (14–16 ). HDI and estimated HDI were used to The global prevalence of anaemia was calculated by com- predict the prevalence of anaemia using a multiple regres- bining the estimates for all population groups, which cov- sion model. ered the entire population except for one segment (women

Table 2.2 Prediction equations used to generate anaemia estimates for countries without survey data Population Number of Equation R2 p-value group countries for model Preschool-age 82 = 3.5979-4.9093*HDIb-0.0657*Exp on health–0.0003*Exp on health 0.550 <0.0001 childrena per capita–0.0009*Adult Female mortality School-age 35 = 1.4248-2.6894*HDI+0.0087*Urban population- 0.583 <0.0001 children 0.0129*Imm Measles-0.0005*Exp on health per capita Non-pregnant 79 = 0.9475–2.3447*HDI+0.1643*Population growth rate–0.0697 0.453 <0.0001 women exp on health Pregnant 60 = 2.7783-2.8352*HDI-0.0085*Imm DTP3–0.0004*Exp on health 0.323 <0.0001 women per capita–0.0017*Adult Male mortality Men 32 = 0.0991–4.6160*HDI+0.0209*Imm DTP3-0.0828*Gov Exp on health 0.577 <0.0001 Elderly 13 = -1.6693+0.2872*HDI–0.1359*Exp on health+0.0047*Adult Male mortality 0.385 0.0627 a population groups: Preschool-age children (0.00–4.99 yrs), Pregnant women (no age range defined), Non-pregnant women (15.00–49.99 yrs), School-age children (5.00–14.99 yrs), Men (15.00–59.99 yrs), Elderly (≥60.00 yrs). b hdI = United Nations Human Development Index, Exp= expenditure, Imm DTP3 = immunization for diphtheria, tetanus and pertussis.

2. Methods 5 50.00–59.99 yrs). The estimate of anaemia prevalence in 2.4 Population coverage, proportion of the elderly was applied to this segment of the population. population, and the number of individuals Because the median age of menopause in women is approx- with anaemia imately 50.5 yrs (21), menstrual iron losses have stopped for 2.4.1 Population coverage the majority of women in this age group, and we considered The population covered by survey data at the regional and that the prevalence of anaemia may be more similar to the global level was calculated by summing the number of in- elderly than to women of reproductive age. Furthermore, dividuals in the population group in countries with sur- the data from the National Health and Nutrition Examina- vey data divided by the total number of individuals in the tion Survey (NHANES) in the United States of America population group in the entire region or globally for each were compared among women 20–49 yrs, 50–59 yrs, and population group. 60+ yrs, and women 50–59 yrs had a Hb distribution more Coverage when including countries with a regression- similar to women 60+ yrs than to women 20–49 yrs.1 In based estimate is not presented, since it was similar for all addition, the distribution of C-reactive protein (CRP) population groups and included all countries except for one was most similar between women 50–59 yrs and women (99.7–99.9%). 60+ yrs. However, the proportion of anaemia attributable to elevated CRP in women 50–59 yrs was more similar to 2.4.2 Proportion of population and the number of women 20–49 yrs. individuals affected The number of individuals with anaemia was estimated in 2.3.6 Classification of anaemia as a problem of public each population group for each country and each group- health significance ing of countries based on each country’s proportion of the The prevalence of Hb values below the population-specific population with anaemia. The proportion of the population Hb threshold was used to classify countries by the level of group with anaemia was multiplied by the national popula- the public health problem (Table 2.3) (2). tion to provide the number of subjects with anaemia at the country level, and the 95% confidence interval was used as a measure of uncertainty. The population figures are for the Table 2.3 Classification of anaemia as a problem of public 2006 projection from the 2004 revision of the United Na- health significance tions population estimates (22). Population figures for preg- Prevalence of Category of public anaemia (%) health significance nant women were derived from the total number of births (time period 2005–2010) by assuming one child per woman ≤4.9 no public health problem per year, not taking into account spontaneous and induced 5.0–19.9 mild public health problem 20.0–39.9 moderate public health problem abortions. For 15 countries with a small total population ≥40.0 Severe public health problem (0.01% of all women), birth data were not provided in tabu- Source: adapted from reference (2) lations of the UN population division, and the number of pregnant women was estimated by applying a WHO regional average of births per reproductive-age woman (15.00 to 49.99 yrs) to the total number of reproductive-age women.

1 M. Cogswell, unpublished data, 2006.

6 worldwide prevalence of anaemia 1993–2005 3. Results and Discussion

3.1 Results 3.1.2 Proportion of population and number of 3.1.1 Population coverage individuals with anaemia Almost the entire population was covered by survey data Globally, anaemia affects 1.62 billion people (95% CI: or regression-based estimates, since all countries except 1.50–1.74 billion), which corresponds to 24.8% of the pop- for one had an estimate. The proportion of the population ulation (95% CI: 22.9–26.7%) (Table 3.2). The highest covered by survey data was high for preschool-age children prevalence is in preschool-age children (47.4%, 95% CI: (76.1%) and pregnant (69.0%) and non-pregnant women 45.7–49.1), and the lowest prevalence is in men (12.7%, (73.5%), but lower for school-age children (33.0%), men 95% CI: 8.6–16.9%). However, the population group with (40.2%), and the elderly (39.1%) (Table 3.1). By WHO the greatest number of individuals affected is non-pregnant region, the coverage was highest in the Western Pacific and women (468.4 million, 95% CI: 446.2–490.6). lowest in Europe. Based on this population coverage, it was WHO regional estimates generated for preschool-age decided that there were insufficient data in school-age chil- children and pregnant and non-pregnant women indi- dren, men, and the elderly to generate regional estimates. cate that the highest proportion of individuals affected are in Africa (47.5–67.6%), while the greatest number af-

Table 3.1 Population coverage (%) by anaemia prevalence surveys (national or subnational) conducted between 1993 and 2005 WHO region PreSACa PW NPW SAC Men Elderly All Africa (46)b 74.6 (26)c 65.8 (22) 61.4 (23) 13.2 (8) 21.9 (11) 0.0 (0) 40.7 Americas (35) 76.7 (16) 53.8 (15) 56.2 (13) 47.1 (9) 34.3 (2) 47.6 (1) 58.0 South-East Asia (11) 85.1 (9) 85.6 (8) 85.4 (10) 13.6 (3) 4.1 (2) 5.2 (1) 14.9 Europe (52) 26.5 (12) 8.3 (4) 28.0 (12) 9.3 (3) 14.1 (3) 8.0 (2) 22.9 Eastern Mediterranean (21) 67.4 (11) 58.7 (7) 73.5 (11) 15.5 (6) 27.5 (6) 3.2 (3) 84.3 Western Pacific (27) 90.4 (10) 90.2 (8) 96.9 (13) 83.1 (7) 96.2 (10) 93.3 (6) 13.8 Global (192) 76.1 (84) 69.0 (64) 73.5 (82) 33.0 (36) 40.2 (34) 39.1 (13) 48.8 a population groups: PreSAC, preschool-age children (0.00–4.99 yrs); PW, pregnant women (no age range defined);NPW , non-pregnant women (15.00–49.99 yrs), SAC, school-age children (5.00–14.99 yrs), Men (15.00–59.99 yrs), Elderly (≥60.00 yrs). b number of countries in each grouping. c Total number of countries with data, no figure is provided forA ll since each country may be partially covered by some population groups, but few countries have data on all 6 population groups and no countries have data for women 50–59 yrs of age.

Table 3.2 Global anaemia prevalence and number of individuals affected Population group Prevalence of anaemia Population affected Percent 95% CI Number (million) 95% CI Preschool-age children 47.4 45.7–49.1 293 283–303 School-age children 25.4 19.9–30.9 305 238–371 Pregnant women 41.8 39.9–43.8 56 54–59 Non-pregnant women 30.2 28.7–31.6 468 446–491 Men 12.7 8.6–16.9 260 175–345 Elderly 23.9 18.3–29.4 164 126–202 Total population 24.8 22.9–26.7 1620 1500–1740

3. Results and Discussion 7 Table 3.3 Anaemia prevalence and number of individuals affected in preschool-age children, pregnant women, and non-pregnant women in each WHO region WHO region Preschool-age childrena Pregnant women Non-pregnant women Prevalence # affected Prevalence # affected Prevalence # affected (%) (millions) (%) (millions) (%) (millions) Africa 67.6 83.5 57.1 17.2 47.5 69.9 (64.3–71.0)b (79.4–87.6) (52.8–61.3) (15.9–18.5) (43.4–51.6) (63.9–75.9) Americas 29.3 23.1 24.1 3.9 17.8 39.0 (26.8–31.9) (21.1–25.1) (17.3–30.8) (2.8–5.0) (12.9–22.7) (28.3–49.7) South-East 65.5 115.3 48.2 18.1 45.7 182.0 Asia (61.0–70.0) (107.3–123.2) (43.9–52.5) (16.4–19.7) (41.9–49.4) (166.9–197.1) Europe 21.7 11.1 25.1 2.6 19.0 40.8 (15.4–28.0) (7.9–14.4) (18.6–31.6) (2.0–3.3) (14.7–23.3) (31.5–50.1) Eastern 46.7 0.8 44.2 7.1 32.4 39.8 Mediterranean (42.2–51.2) (0.4–1.1) (38.2–50.3) (6.1–8.0) (29.2–35.6) (35.8–43.8) Western 23.1 27.4 30.7 7.6 21.5 97.0 Pacific (21.9–24.4) (25.9–28.9) (28.8–32.7) (7.1–8.1) (20.8–22.2) (94.0–100.0) Global 47.4 293.1 41.8 56.4 30.2 468.4 (45.7–49.1) (282.8–303.5) (39.9–43.8) (53.8–59.1) (28.7–31.6) (446.2–490.6) a population subgroups: Preschool-age children (0.00–4.99 yrs); Pregnant women (no age range defined); Non-pregnant women (15.00–49.99 yrs). b 95% Confidence Intervals. fected are in South-East Asia where 315 million (95% CI: 3.2 Discussion 291–340) individuals in these three population groups are 3.2.1 Population coverage affected (Table 3.3). The population covered by survey data is high for the three population groups considered to be the most vulnerable; 3.1.3 Classification of countries by degree of public preschool-age children, pregnant women, and non-pregnant health significance of anaemia women of childbearing age. A greater number of countries There are almost no countries where anaemia is not at least have undertaken surveys to assess anaemia in non-pregnant a mild public health problem in all three of the population women than in pregnant women. However, since some of groups for which country-level estimates were generated the surveys conducted in pregnant women are from coun- (Table 3.4). For pregnant women, over 80% of the countries with a large population, the proportion of the global tries have a moderate or severe public health problem. population covered by these surveys is similar between the The level of the public health problem across countries is two population groups. illustrated by maps for preschool-age children and pregnant and non-pregnant women in Figure 3.1. 3.2.2 Strengths of estimates These estimates are based on a high proportion of nation- Table 3.4 Number of countries categorized by public ally representative survey data. For the three most vulner- health significance of anaemia able population groups, preschool-age children, pregnant Public Preschool-age Pregnant Non-pregnant women, and non-pregnant women, nationally representative health childrenb women women data covered more than two thirds of the population in each problema Number of countries number of countries number of countries group. This eliminates the bias that comes from local data, None 2 0 1 which may greatly over- or under-represent the national Mild 40 33 59 situation. Moderate 81 91 78 Severe 69 68 54 Regression-based estimates were used for countries without data, and these estimates explained a large amount of a the prevalence of anaemia as a public health problem is categorized as follows: <5%, no public health problem; 5–19.9%, mild public health problem; 20–39.9%, the variation in anaemia prevalence among countries with moderate public health problem; ≥40%, severe public health problem. b population groups: Preschool-age children (0.00–4.99 yrs); Pregnant women (no survey data (32–58%). age range defined); Non-pregnant women (15.00–49.99 yrs). 3.2.3 Limitations of estimates There were fewer surveys that collected data in school-age children, men, and the elderly, and in some cases there were no data for an entire region. Thus, country- or regional-

8 worldwide prevalence of anaemia 1993–2005 3. Results Discussion and Figure 3.1a Anaemia as a public health problem by country: Preschool-age children

Category of public health significance (anaemia prevalence) Normal (<5.0%) Mild (5.0–19.9%) Moderate (20.0–39.9%) Severe (>40.0%)_ No data 9 10 Figure 3.1b Anaemia as a public health problem by country: Pregnant women worldw i de prevalence of anaem of prevalence de Category of public health significance (anaemia prevalence) Normal (<5.0%) Mild (5.0–19.9%) Moderate (20.0–39.9%) Severe (>40.0%)_ No data i a 1993–2005 3. Results Discussion and Figure 3.1c Anaemia as a public health problem by country: Non-pregnant women of reproductive age

Category of public health significance (anaemia prevalence) Normal (<5.0%) Mild (5.0–19.9%) Moderate (20.0–39.9%) Severe (>40.0%)_ No data 11 level estimates for these population groups were not pre- the main burden is concentrated in South-East Asia, where sented. Even the global estimates should be interpreted about 40% of anaemic preschool-age children and non- with caution since they are based primarily on regression- pregnant women, and about 30% of pregnant women re- based estimates for these population groups. side. Furthermore, the estimates generated for women (50–59 yrs) were not based on any data from this population group 3.2.5 Classification of countries by degree of public since it is not routinely collected. It is why this estimate was health significance of anaemia, based on used for the global figure only and not as an estimate for haemoglobin concentration this group of women. Anaemia is a public health problem for pregnant women These estimates were based on a number of assumptions. in all of WHO’s Member States. Given the consequences All surveys were treated equally, although in fact their qual- of anaemia during pregnancy, this problem urgently needs ity varied greatly. For example, some surveys used sampling to be addressed. The situation is similar in preschool-age proportionate to the population distribution within the children and non-pregnant women for whom only one or country, while others did not, and in some national sur- two countries do not have an anaemia public health prob- veys, specific areas had to be left out due to security or ac- lem. For women and young children, the majority of WHO cessibility issues. Furthermore for some population groups Member States (132 to 159, depending on the population (e.g., children 0.5–4.99 yrs), the population sampled cov- group) have a moderate-to-severe public health problem ered only a portion of the desired age range (e.g., children with anaemia; meaning that over 20% of the population 1–1.99 yrs). For the purpose of our analysis, these surveys group in these countries is affected. This should draw the were considered equal to those that covered the entire age attention of the public health authorities on the need to range. However, an estimate from children in only the low- re-evaluate current strategies to control anaemia by mak- er or higher end of the range would significantly impact ing sure that the various factors contributing to anaemia the prevalence estimate, since children below two years of have been identified and addressed properly through an in- age are much more likely to be anaemic than those above tegrated approach. this age. While there were only three countries for which sub 3.2.6 Comparison to previous estimates national data were used to generate prevalence estimates in It is a challenge to assess global progress in the control of preschool-age children, these data may result in an over- or anaemia, since the methodology used for these estimates under-estimation of anaemia prevalence for those coun- is so different from those used in previous estimates. Pre- tries. vious global estimates made by DeMaeyer in 1985 indi- In some cases, anaemia prevalence was calculated us- cated that approximately 30% of the world’s population ing Hb concentration and assuming that it was distributed was anaemic (23). These estimates seem to be based on an normally. This may have lead to a slight over-estimation extrapolation of the prevalence in preschool-age children, of anaemia prevalence, since Hb distributions tend to be school-age children, women, and men. These estimates, negatively skewed in populations with a high prevalence of which excluded China where 20% of the global population deficiency. resides, indicated that 43% of preschool-age children, 35% The estimates for pregnant women did not account for of all women, and 51% of pregnant women were anaemic. the trimester of pregnancy since this information is not Current estimates, excluding China, are 52%, 34%, and routinely reported in publications. Prevalence would be 44%, respectively. Variations in the methods employed, expected to vary by trimester, and thus the estimates for and a larger proportion of nationally representative data, pregnant women may have been biased if there was not an are more likely to account for the differences between these even distribution of women at various stages of pregnancy. estimates than a change in anaemia prevalence. Furthermore, we do not have prevalence figures for the In 1992, WHO estimates for the year 1988 indicated third trimester when anaemia is most likely to affect the that 37%, 51%, and 35% of all women and pregnant and risk of maternal mortality. non-pregnant women were anaemic (24). These estimates included subnational data for China. The current estimates 3.2.4 Proportion of population and the number of which use nationally representative data for China (31%, individuals with anaemia 42%, and 30%) may or may not be lower, since the meth- One in four people is affected by anaemia, and pregnant odologies used are substantially different. women and preschool-age children are at the greatest risk. The WHO regions of Africa and South-East Asia have 3.3 Conclusion the highest risk, where about two thirds of preschool-age The data available for these estimates are the most repre- children and half of all women are affected. In numbers, sentative data to date, and we can consider that these esti-

12 worldwide prevalence of anaemia 1993–2005 mates are the most accurate reflection of the global anaemia not routinely collected, the database does not provide in- prevalence published so far. However, countries without formation on the ability of the strategies to address these survey data should be encouraged to collect data, since re- factors. Hopefully, these estimates will encourage countries gression-based estimates are good at the regional and global to plan surveys which assess the prevalence of factors that level, but may not be the most accurate reflection of the contribute to anaemia – not only iron deficiency, but also situation for an individual country. infectious diseases and other micronutrient deficiencies. The generation of these estimates and the maintenance The understanding of how these factors vary by geography, of the anaemia database provide a reliable tool to track level of development, and other social and economic factors the global progress towards the elimination of anaemia will make it easier to design interventions that are more ef- and the effectiveness of the current strategies for anaemia fective and integrative in addressing multiple contributing control. However, since information on causal factors is factors at the same time.

3. Results and Discussion 13 References

1. World Health Organization. The World Health Report 12. Human Development Indicators. In: Cait Murphy BR- 2002: Reducing risks, promoting healthy life. Geneva, L, ed. Human Development Report 2004. New York, World Health Organization, 2002. United Nations Development Programme, 2004: 139– 2. Iron deficiency anaemia: assessment, prevention, and con- 250. trol. A guide for programme managers. Geneva, World 13. World Health Organization. World Health Statistics Health Organization, 2001 (WHO/NHD/01.3). 2005. Geneva, World Health Organization, 2005. 3. Macgregor M. Maternal anaemia as a factor in prema- 14. Mathers CD, Loncar D. Projections of global mortality turity and perinatal mortality. Scottish Medical Journal, and burden of disease from 2002 to 2030. PLoS Medi- 1963, 8:134. cine, 2006, 3:e442. 4. Scholl TO, Hediger ML. Anemia and iron-deficiency 15. World Health Organization. The World Health Report anemia: compilation of data on pregnancy outcome. 2000: Health systems: improving performance. Geneva, American Journal of Clinical Nutrition, 1994, 59:492S– World Health Organization, 2000. 500S. 16. World Health Organization. The World Health Report: 5. Bothwell T, Charlton R, eds. Iron deficiency in women. 2004: Changing History. Geneva, World Health Or- Washington DC, Nutrition Foundation, 1981. ganization, 2004. 6. Guidelines for the treatment of malaria. Geneva, Roll 17. Wackerly D, Mendenhall W, Scheaffer RL. Math- Back Malaria Department, World Health Organiza- ematical Statistics with Applications, 6th edition. Pacific tion, 2006 (WHO/HTM/MAL/2006.1108). Grove, CA, Duxbury Press, 2001. 7. Crompton DWT et al., eds. Controlling disease due to 18. Lohr SL. Sampling: Design and Analysis, 1st edition. helminth infections. Geneva, World Health Organiza- Pacific Grove, CA, Duxbury Press, 1998. tion, 2003. 19. Neter J et al. Applied Linear Statistical Models, 4th edi- 8. Koller O. The clinical significance of hemodilution tion. New York, McGraw-Hill/Irwin, 1996. during pregnancy. Obstetrical and Gynecological Survey, 20. Allison PD. Logistic Regression using the SAS System. In- 1982, 37:649–652. dianapolis, IN, WA (Wiley-SAS), 2001. 9. Nordenberg D, Yip R, Binkin NJ. The effect of ciga- 21. Whelan EA et al. Menstrual and reproductive charac- rette smoking on hemoglobin levels and anemia screen- teristics and age at natural menopause. American Jour- ing. Journal of the American Medical Association, 1990, nal of Epidemiology, 1990, 131:625–632. 264 :1556 –1559. 22. United Nations PD. World Population Prospects – the 10. Hurtado A., Merino C, Delgado E. Influence of anox- 2004 revision. New York, 2005. emia on haematopoietic activities. Archives of Internal 23. DeMaeyer E, Adiels-Tegman M. The prevalence of Medicine, 1945, 75:284–323. anaemia in the world. World Health Statistics Quarterly, 11. Human Development Report 2002, Deepening democ- 1985, 38:302–316. racy in a fragmented world. New York, United Nations 24. World Health Organization. The Prevalence of Anae- Development Programme, 2002. mia in Women: A Tabulation of Available Information. 1992 (WHO/MCH/MSM/92.2).

14 worldwide prevalence of anaemia 1993–2005 Annex 1 WHO Member States grouped by WHO region as of 2005

Table A1.1 WHO Member States grouped by WHO region Africa Sierra Leone Saint Vincent and the Bulgaria Algeria South Africa Grenadines Croatia Angola Swaziland Suriname Cyprus Benin Togo Trinidad and Tobago Czech Republic Botswana Uganda United States of America Denmark Burkina Faso United Republic of Uruguay Estonia Burundi Tanzania Venezuela (Bolivarian Finland Cameroon Zambia Republic of) France Cape Verde Zimbabwe Georgia Central African Republic South-East Asia Germany Chad Americas Bangladesh Greece Comoros Antigua and Barbuda Bhutan Hungary Congo Argentina Democratic People’s Iceland Côte d’Ivoire Bahamas Republic of Korea Ireland Democratic Republic of Barbados India Israel the Congo Belize Indonesia Italy Equatorial Guinea Bolivia Maldives Kazakhstan Eritrea Brazil Myanmar Kyrgyzstan Ethiopia Canada Nepal Latvia Gabon Chile Sri Lanka Lithuania Gambia Colombia Thailand Luxembourg Ghana Costa Rica Timor-Leste Malta Guinea Cuba Monaco Guinea-Bissau Dominica Europe Netherlands Kenya Dominican Republic Albania Norway Lesotho Ecuador Andorra Poland Liberia El Salvador Armenia Portugal Madagascar Grenada Austria Republic of Moldova Malawi Guatemala Azerbaijan Romania Mali Guyana Belarus Russian Federation Mauritania Haiti Belgium San Marino Mauritius Honduras Bosnia and Herzegovina Serbia and Montenegro1 Mozambique Jamaica 1 Mexico On 3 June 2006, the Permanent Representative of the Republic of Serbia Namibia to the United Nations and other International Organizations in Geneva Niger Nicaragua informed the Acting Director-General of the WHO that “the mem- Nigeria Panama bership of the state union Serbia and Montenegro in the United Na- tions, including all organs and the organizations of the United Nations Rwanda Paraguay system, is continued by the Republic of Serbia on the basis of Article Sao Tome and Principe Peru 60 of the Constitutional Charter of Serbia and Montenegro, activated by the Declaration of Independence adopted by the National Assembly Senegal Saint Kitts and Nevis of Montenegro on 3 June 2006”. Estimates used or referred to in this Seychelles Saint Lucia document cover a period of time preceding that communication.

Annex 1 15 Slovakia Eastern Mediterranean Syrian Arab Republic Marshall Islands Slovenia Afghanistan Tunisia Micronesia (Federated Spain Bahrain United Arab Emirates States of) Sweden Djibouti Yemen Mongolia Switzerland Egypt Nauru Tajikistan Iran (Islamic Republic of) Western Pacific New Zealand The former Yugoslav Iraq Australia Niue Republic of Macedonia Jordan Brunei Darussalam Palau Turkey Kuwait Cambodia Papua New Guinea Turkmenistan Lebanon China Philippines Ukraine Libyan Arab Jamahiriya Cook Islands Republic of Korea United Kingdom of Great Morocco Fiji Samoa Britain and Northern Oman Japan Singapore Ireland Pakistan Kiribati Solomon Islands Uzbekistan Qatar Lao People’s Democratic Tonga Saudi Arabia Republic Tuvalu Somalia Malaysia Vanuatu Sudan Viet Nam

Table A1.2 WHO Member States grouped by UN region and subregion1

Africa Gabon Niger Pakistan Eastern Africa Sao Tome and Principe Nigeria Sri Lanka Burundi Senegal Comoros Northern Africa Sierra Leone South-eastern Asia Djibouti Algeria Togo Brunei Darussalam Eritrea Egypt Lao People’s Democratic Ethiopia Libyan Arab Jamahiriya Asia Republic Kenya Morocco Central Asia Malaysia Madagascar Sudan Kazakstan Myanmar Malawi Tunisia Kyrgyzstan Philippines Mauritius Tajikistan Singapore Mozambique Southern Africa Turk menistan Thailand Rwanda Botswana Uzbekistan Timor-Leste Seychelles Lesotho Viet Nam Somalia Namibia Eastern Asia Uganda South Africa China Western Asia United Republic of Swaziland Democratic People’s Armenia Tanzania Republic of Korea Azerbaijan Zambia Western Africa Japan Bahrain Zimbabwe Benin Mongolia Cyprus Burkina Faso Republic of Korea Georgia Middle Africa Cape Verde Iraq Angola Côte d’Ivoire Southern Asia Israel Cameroon Gambia Afghanistan Jordan Central African Republic Ghana Bangladesh Kuwait Chad Guinea Bhutan Lebanon Congo Guinea-Bissau India Oman Democratic Republic of Liberia Iran (Islamic Republic of) The Congo Mali Maldives Equatorial Guinea Mauritania Nepal

1 http://unstats.un.org/unsd/methods/m49/m49regin.htm

16 worldwide prevalence of anaemia 1993–2005 Qatar Southern Europe Cuba Uruguay Saudi Arabia Albania Dominica Venezuela (Bolivarian Syrian Arab Republic Andorra Dominican Republic Republic of) Turkey Bosnia and Herzegovina Grenada United Arab Emirates Croatia Haiti Northern America Yemen Greece Jamaica Canada Italy Saint Kitts and Nevis United States of America Europe Malta Saint Lucia Eastern Europe Portugal Saint Vincent and the Oceania Belarus San Marino Grenadines Australia-New Zealand Bulgaria Serbia and Montenegro Trinidad and Tobago Australia Czech Republic Slovenia New Zealand Hungary Spain Central America Poland The former Yugoslav Belize Melanesia Republic of Moldova Republic of Macedonia Costa Rica Fiji Romania El Salvador Papua New Guinea Russian Federation Western Europe Guatemala Solomon Islands Slovakia Austria Honduras Vanuatu Ukraine Belgium Mexico France Nicaragua Micronesia Northern Europe Germany Panama Kiribati Denmark Luxembourg Marshall Islands Estonia Monaco South America Micronesia (Federated Finland Netherlands Argentina States of) Iceland Switzerland Bolivia Nauru Ireland Brazil Palau Latvia Americas Chile Lithuania Latin America and Colombia Polynesia Norway the Caribbean Ecuador Cook Islands Sweden Caribbean Guyana Niue United Kingdom of Great Antigua and Barbuda Paraguay Samoa Britain and Northern Bahamas Peru Tonga Ireland Barbados Suriname Tuva lu

Annex 1 17 Annex 2 Results by UN region

Table A2.1 Population coverage (%) by anaemia prevalence surveys (national or subnational) conducted between 1993 and 2005, by UN region UN region PreSACa PW NPW SAC Men Elderly All Africa (53)b 76.7 (30)c 65.3 (25) 63.6 (26) 18.6 (10) 32.0 (14) 1.8 (1) 40.7 Asia (47) 82.1 (30) 80.9 (21) 88.8 (34) 37.0 (11) 47.6 (13) 54.1 (7) 58.0 Europe (41) 19.2 (5) 0.9 (1) 23.9 (5) 12.9 (3) 15.9 (2) 8.7 (2) 14.9 L Am and the Caribbean (33) 70.5 (15) 38.4 (14) 37.5 (12) 28.9 (8) 0.1 (1) 0.0 (0) 22.9 N America (2) 92.4 (1) 92.8 (1) 89.9 (1) 91.3 (1) 89.9 (1) 89.6 (1) 84.3 Oceania (16) 5.1 (3) 4.7 (2) 16.5 (4) 15.1 (3) 15.6 (3) 15.1 (2) 13.8 Global (192) 76.1 (84) 69.0 (64) 73.5 (82) 33.0 (36) 40.2 (34) 39.1 (13) 48.8 a population groups: PreSAC, preschool-age children (0.00–4.99 yrs); PW, pregnant women (no age range defined);NPW , non-pregnant women (15.00–49.99 yrs), SAC, school-age children (5.00–14.99 yrs), Men (15.00–59.99 yrs), Elderly (≥60.00 yrs). b number of countries in each grouping. c total number of countries with data. No figure is provided for A‘ ll’ since each country may be partially covered by some population groups, but few countries have data on all 6 population groups and no countries have data for women 50–59 yrs of age.

Table A2.2 Anaemia prevalence and number of individuals affected in preschool-age children, pregnant women, and non-pregnant women in each UN region UN regiona Preschool-age childrenb Pregnant women Non-pregnant women Prevalence # affected Prevalence # affected Prevalence # affected (%) (millions) (%) (millions) (%) (millions) Africa 64.6 93.2 55.8 19.3 44.4 82.9 (61.7–67.5)c (89.1–97.4) (51.9–59.6) (18.0–20.7) (40.9–47.8) (76.5–89.4) Asia 47.7 170.0 41.6 31.7 33.0 318.3 (45.2–50.3) (161.0–178.9) (39.0–44.2) (29.7–33.6) (31.3–34.7) (302.0–334.6) Europe 16.7 6.1 18.7 1.4 15.2 26.6 (10.5–23.0) (3.8–8.4) (12.3–25.1) (0.9–1.8) (10.5–19.9) (18.4–34.9) LAC 39.5 22.3 31.1 3.6 23.5 33.0 (36.0–43.0) (20.3–24.3) (21.8–40.4) (2.5–4.7) (15.9–31.0) (22.4–43.6) NA 3.4 0.8 6.1 0.3 7.6 6.0 (2.0–4.9) (0.4–1.1) (3.4–8.8) (0.2–0.4) (5.9–9.4) (4.6–7.3) Oceania 28.0 0.7 30.4 0.2 20.2 1.5 (15.8–40.2) (0.4–1.0) (17.0–43.9) (0.1–0.2) (9.5–30.9) (0.7–2.4) Global 47.4 293.1 41.8 56.4 30.2 468.4 (45.7–49.1) (282.8–303.5) (39.9–43.8) (53.8–59.1) (28.7–31.6) (446.2–490.6) a un regions: Africa, Asia, Europe, Latin America and the Caribbean (LAC), Northern America (NA), and Oceania. b population groups: PreSAC, preschool-age children (0.00–4.99 yrs); PW, pregnant women (no age range defined); NPW, non-pregnant women (15.00–49.99 yrs). c 95% Confidence Intervals.

18 worldwide prevalence of anaemia 1993–2005

20 Annex 3 National estimates of anaemia Table A3.1 Country estimates of anaemia prevalence in preschool-age children Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<110 g/L (number of individuals)(000) 0–4.99y General Date of survey Level of Sample Public health (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Afghanistan 5732 31082 2004 n 0.50–4.99 870 5173 adjusted for altitude 37.9 33.5–42.6 2172 1918–2439 moderate Albania 252 3147 R 31.0 9.4–65.9 78 24–166 moderate Algeria 3218 33354 R 42.5 14.7–76.1 1369 473–2448 severe Andorra 4 67 R 12.0 2.9–38.4 0 0–1 mild Angola 3058 16400 1998–1999 n 0.00–4.99 825 2839 29.7 25.5–34.3 908 779–1048 moderate Antigua and Barbuda 8 82 1996–1997 n 1.00–4.99 81 3758 sample size <100 49.4 34.5–64.4 4 3–5 severe Argentina 3346 39134 R 18.1 4.8–49.2 605 160–1646 mild Armenia 162 3007 2000 n 0.50–4.99 1334 3208 adjusted for altitude 23.9 20.8–27.3 39 34–44 moderate Australia 1252 20366 R 8.0 1.8–29.6 101 22–371 mild Austria 379 8205 R 10.5 2.5–35.3 40 9–134 mild Azerbaijan 604 8471 2001 n 1.00–4.99 2017 4682 31.8 29.0–34.7 192 175–210 moderate Bahamas 30 327 R 21.9 6.1–54.8 7 2–17 moderate Bahrain 64 739 R 24.7 7.0–58.9 16 4–38 moderate Bangladesh 17491 144437 2001 n 0.50–4.99 1148 3256 national survey in rural areas 47.0 42.9–51.1 8221 7512–8937 severe Barbados 16 270 R 17.1 4.5–47.3 3 1–8 mild Belarus 452 9700 R 27.4 8.1–61.9 124 37–280 moderate Belgium 559 10437 R 8.7 2.0–31.0 48 11–173 mild Belize 34 275 R 35.9 11.6–70.6 12 4–24 moderate Benin 1478 8703 2001 n 0.50–4.99 2284 3461 adjusted for altitude 81.9 79.6–84.0 1210 1176–1242 severe Bhutan 297 2211 2002 n 0.50–5.07 100 5150 1800 subjects recruted, final 80.6 67.3–89.3 239 200–265 severe sample size not specified, adjusted for altitude. Bolivia 1243 9354 2003–2004 n 0.50–4.99 2693 5095 51.6 48.9–54.3 641 608–675 severe Bosnia and Herzegovina 182 3912 R 26.8 7.6–61.9 49 14–113 moderate

worldw Botswana 215 1760 1994 n 0.50–4.99 149 2805 38.0 27.7–49.5 82 60–106 moderate Brazil 18074 188883 1993, 1997, 1998 f ns 4.99 6556 2375, prevelance pooled from three 54.9 53.2–56.6 9923 9614–10229 severe 2843, studies at state level 614 i de prevalence of anaem of prevalence de Brunei Darussalam 40 382 R 24.2 6.8–58.5 10 3–24 moderate Bulgaria 334 7671 R 26.7 7.8–61.1 89 26–204 moderate Burkina Faso 2527 13634 2003 n 0.50–4.99 2786 4948 91.5 89.9–92.9 2313 2273–2347 severe Burundi 1394 7834 2003 n 0.00–4.99 1150 5782 56.0 51.9–60.0 780 723–836 severe Cambodia 1869 14351 2000 n 0.50–4.99 1461 3206 63.4 59.8–66.8 1185 1118–1249 severe Cameroon 2465 16601 2004 n 0.50–4.99 3530 5214 adjusted for altitude 68.3 66.1–70.4 1684 1629–1736 severe Canada 1691 32566 R 7.6 1.6–28.9 129 28–489 mild Cape Verde 73 519 R 39.7 13.3–73.8 29 10–54 moderate Central African Republic 644 4093 1999 n 0.50–2.99 1055 1722 84.2 80.8–87.1 542 520–561 severe Chad 1927 10032 R 71.1 36.0–91.5 1370 694–1763 severe i

a 1993–2005 Chile 1233 16465 R 24.4 6.9–58.2 301 86–718 moderate China 83929 1331217 2002 n 0.00–4.99 15073 5287 weighted prevalence 20.0 19.1–20.9 16786 16041–17556 moderate Colombia 4718 46279 R 27.7 8.1–62.4 1307 383–2945 moderate Comoros 129 819 R 65.4 30.0–89.2 84 39–115 severe Congo 773 4117 R 66.4 31.0–89.7 513 240–693 severe Cook Islands 2 18 R 24.7 7.0–58.8 0 0–1 moderate problem Public health 2–3 m oderate 1–6 m oderate 0–6 m ild

2–25 m ild 4–37 m oderate 7–103 m ild 12–69 s evere 30–41 m oderate 8–103 m ild 27–44 s evere 7–109 m ild 65–102 m oderate 13–116 m oderate 52–415 m oderate 22–226 m ild 37–108 s evere 30–150 s evere 32–177 s evere 15–196 m ild 24–237 m ild 95% CI 483–586 m oderate 111–699 m oderate 135–162 m ild 269–710 s evere 69–1135 m ild 177–193 s evere 60–1022 m oderate 738–824 m oderate 129–298 s evere 725–783 s evere 276–313 m oderate 946–2533 s evere 180–1043 m oderate 695–4328 m oderate 974–3702 s evere 7967–8407 s evere 2543–2877 m oderate 2311–2446 s evere 1225–1321 s evere 5403–12347 s evere 3378–16758 s evere 88059–90100 s evere 9 3 3 2 82 48 84 29 79

37 15 36 32 86 96 62 35 89 32 Population with anaemia Population 180 533 349 546 148 544 310 185 273 781 240 755 294 1928 8191 2707 9979 2380 1276 9608 2174 2440 (number of individuals)(000) Estimate 89090

95% CI 6.6–56.9 7.7–61.5 5.0–49.9 4.9–49.6 2.0–32.1 6.5–57.0 2.8–37.1 1.8–30.5 1.7–29.3 3.0–38.3 9.9–66.8 5.0–50.1 1.7–29.2 2.4–35.2 16.6–25.9 33.9–90.6 28.7–34.8 68.7–72.5 30.7–89.3 24.8–45.5 11.0–69.4 12.5–72.4 28.1–31.8 16.7–20.2 13.7–75.9 34.4–90.9 40.7–93.1 33.3–45.2 15.7–77.5 75.8–82.6 13.7–74.7 73.9–78.2 36.0–40.2 75.9–81.8 40.3–93.0 36.5–59.5 62.7–67.8 28.1–31.8 73.4–75.1 15.6–77.6 11.2–69.8 22.3–84.8 with Hb<110 g/L

9.0 8.3 Proportion of the population 7.8 7.8 20.9 31.7 34.4 29.9 18.4 39.1 79.4 76.1 38.1 79.0 47.9 65.3 29.9 74.3 69.0 23.4 26.7 18.6 18.4 70.6 65.8 34.6 37.9 40.8 69.6 23.4 75.2 11.5 44.5 40.6 12.1 32.0 74.9 18.8 44.5 35.0 55.9 10.3 Estimate

ooled data disaggregated by by ooled data disaggregated Notes age, adjusted for altitude. age, exclusion for accessibility prevalence calculated for prevalence recommended H b cut-off; adjusted for altitude survey and one state survey excluded from it and completed later, adjust- from it and completed later, ment for altitude.

c 3555 p 3090 71% of population, s urvey covers 5764 3758 1940 5171 a djusted for altitude 2699 2806 4943 4586 pooled, age by d ata disaggregated 2780 3094 3264 a djusted for altitude 3096 2972, 2972, pooled from national p revalence 3780a Reference

Size 590 157 512 140 Sample 1787 4435 4708 3882 1111 2992 4016 1446 2751 4605 20221 Survey Information

Age range 1.00–4.99 0.50–6.99 0.00–4.99 1.00–4.99 0.50–4.99 1.00–4.99 0.50–4.99 1.00–5.99 0.50–4.99 0.50–4.99 0.50–4.99 0.00–4.99 0.50–4.99 1.00–4.99 0.50–2.99

survey Level of

1996 n 1998 n 2005 n 2000 n 1993 n 1999 n 2003 n 2002 n 2000 n 2000 n 2001 n 2000 (years) Date of survey 1996–1997 n 2002–2003 n 1996–1997 n 1998–1999, 1998–1999, F n ,

a 80 845 R 807 R 515 R 854 104 R 752 297 R 4399 4556 R 5446 R 9021 R 6999 4560 R 1325 R 5262 R 1406 R 1556 4434 R 9603 1634 R 8650 7362 4210 R (000) General 18454 R 11294 R 10209 R 22583 59320 13419 R 75437 79289 R 60723 R 82716 R 22556 11140 R 12911 10071 R 70324 R 29551 R 225465 R

1119538

7 Population 2006 Population 49 91 66 91 10 73 21 393 205 674 455 322 121 805 782 278 193 233 237 511 320 984 474 310 (000) 2794 1682 1008 1440 9054 3723 3489 3128 2049 1615 1156 6204 4364 0–4.99y 11602 13269 21598 119906 Country estimates of anaemia prevalence in preschool-age children eople’s R epublic eople’s iji inland C osta R ica

C ote d’Ivoire C roatia C uba C yprus C zech R epublic D emocratic P of Korea D emocratic R epublic of C ongo D enmark D jibouti D ominica D ominican R epublic E cuador E gypt E l S alvador E quatorial Guinea E ritrea E stonia E thiopia F F F rance Gabon Gambia Georgia Germany Ghana Greece Grenada Guatemala

Guinea Guinea-Bissau Guyana H aiti H onduras H ungary Iceland India

Indonesia Iran (Islamic R epublic of) Iraq Ireland

A3.1 Table Member State

Annex 3 21 22 Table A3.1 Country estimates of anaemia prevalence in preschool-age children Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<110 g/L (number of individuals)(000) 0–4.99y General Date of survey Level of Sample Public health (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Israel 669 6847 R 11.8 2.9–37.7 79 19–253 mild Italy 2658 58140 R 10.9 2.6–36.1 291 69–959 mild Jamaica 254 2662 1997–1998 n 1.00–4.99 272 3093 48.2 39.9–56.6 123 102–144 severe Japan 5840 128219 R 10.6 2.5–35.2 617 146–2056 mild Jordan 732 5837 2002 n 0.50–4.99 2573 3389, prevalence pooled from two 28.3 25.9–30.8 207 190–225 moderate 4382 national surveys carried out in the same year, adjusted for altitude (3389 only). Kazakhstan 1073 14812 1999 n ns–4.99 574 2675 36.3 30.9–42.0 390 332–451 moderate Kenya 5927 35106 1999 n 0.17–5.99 2734 3442 data disaggregated by age pooled, 69.0 66.5–71.4 4089 3941–4231 severe adjusted for altitude. Kiribati 12 101 R 41.9 14.2–75.8 5 2–9 severe Kuwait 247 2765 1998–2002 n 0.50–4.99 3693 4375 data disaggregated by sex pooled, 32.4 30.3–34.6 80 75–85 moderate prevalence calculated from mean Kyrgyzstan 543 5325 1997 n ns–2.99 1021 2295 adjusted for altitude 49.8 45.5–54.1 270 247–294 severe Lao People’s Democratic Republic 906 6058 2000 n 0.00–5.99 100 770 48.2 34.8–61.8 437 315–560 severe Latvia 102 2295 R 26.7 7.7–61.1 27 8–62 moderate Lebanon 320 3614 1997–1998 n 1.00–4.99 234 3221 prevalence pooled from data 28.3 20.9–37.1 90 67–119 moderate disaggregated by age, adjusted for altitude. Lesotho 229 1791 2004–2005 n 0.50–4.99 1435 5356 adjusted for altitude 48.6 45.0–52.3 111 103–120 severe Liberia 647 3356 1999 n 0.50–2.99 708 1242 86.7 82.8–89.9 561 536–582 severe Libyan Arab Jamahiriya 649 5968 R 33.9 10.5–69.1 220 68–448 moderate Lithuania 148 3417 R 23.8 6.7–57.5 35 10–85 moderate Luxembourg 29 471 R 9.4 1.9–35.2 3 1–10 mild Madagascar 3149 19105 2003–2004 n 0.50–4.99 1793 5190 adjusted for altitude 68.3 65.2–71.3 2151 2053–2244 severe Malawi 2363 13166 2004–2005 n 0.50–4.99 2173 5201 adjusted for altitude. 73.2 70.5–75.7 1730 1666–1790 severe Malaysia 2725 25796 R 32.4 10.0–67.5 883 271–1841 moderate Maldives 47 337 1994 n ns–4.99 1932 831 81.5 78.9–83.8 38 37–39 severe Mali 2667 13918 2001 n ns–4.99 2826 3446 82.8 80.7–84.7 2208 2153–2258 severe worldw Malta 20 403 R 16.3 4.2–46.4 3 1–9 mild Marshall Islands 8 64 R 30.0 8.7–65.8 2 1–5 moderate Mauritania 539 3158 R 68.2 33.1–90.3 368 178–487 severe i de prevalence of anaem of prevalence de Mauritius 98 1256 1995 n 3.00–6.99 523 395 prevalence pooled from the Islands 16.8 12.7–21.8 16 12–21 mild of Mauritius and Rodrigues Mexico 10726 108327 1998–1999 n 0.50–4.99 5526 2997 data disaggregated by age pooled, 29.4 27.7–31.1 3153 2974–3339 moderate prevalence calculated for recommended cut-off, adjusted for altitude Micronesia (Federated States of) 16 111 1993, 2000 f 2.00–4.99 841 4942, data pooled from 2 surveys at 18.7 15.3–22.7 3 2–4 mild 2548 state level Monaco 2 36 R 5.0 0.9–23.8 0 0–1 mild Mongolia 270 2679 2004 n 0.50–4.99 1241 5247 adjusted for altitude 21.4 18.4–24.8 58 50–67 moderate Morocco 3408 31943 2000 n 0.50–4.99 1486 3469 31.5 28.3–34.9 1073 963–1190 moderate i a 1993–2005 Mozambique 3325 20158 2001–2002 n 0.50–4.99 707 589 74.7 69.9–79.0 2483 2324–2625 severe Myanmar 4586 51009 R 63.2 28.1–88.3 2899 1290–4050 severe Namibia 265 2052 R 40.5 13.4–75.0 107 35–199 severe Nauru 2 14 R 20.0 5.4–52.5 0 0–1 moderate problem Public health 0–4 m oderat 0–0 m oderate 0–1 m oderate 0–2 m oderate 1–8 m oderate 0–0 m ild

3–36 m ild 4–73 m ild 1–10 m oderate 7–11 m oderate 3–17 m oderate 8–100 m ild 14–59 s evere 16–20 m oderate 19–301 m ild 10–106 m ild 94–163 m ild 17–144 m oderate 73–901 m ild 75–546 m oderate 18–220 m ild 28–153 s evere 95% CI 141–220 m oderate 511–943 s evere 147–159 s evere 437–536 m oderate 110–139 m oderate 208–701 s evere 284–513 m ild 285–563 m oderate 576–710 s evere 115–1010 m oderate 571–4496 m oderate 332–2196 m oderate 651–1703 s evere 2775–2909 s evere 1435–2783 s evere 1150–1354 m oderate 4317–4554 s evere 1473–1547 s evere 3335–3816 m oderate 16583–17697 s evere 10509–11214 s evere 2 0 1 1 5 4 9 0 9 84 31 39 59 12 37 18

71 18 83 Population with anaemia Population 178 819 125 153 292 485 124 485 252 410 385 416 642 2844 2377 1249 4443 1510 3572 1959 1067 1310 (number of individuals)(000) Estimate 17159 10862

95% CI 6.7–57.6 2.0–31.3 2.7–36.5 5.0–51.0 6.6–56.9 3.5–41.9 5.7–55.7 1.3–26.3 3.2–39.8 6.1–55.6 9.0–65.3 6.4–56.0 3.1–39.4 7.7–60.9 6.4–56.3 9.9–67.1 1.9–34.0 23.4–36.5 76.1–79.8 51.9–95.8 12.8–22.2 49.1–95.1 73.5–78.5 19.9–82.1 22.2–26.1 48.5–52.5 49.2–52.6 27.0–33.0 82.2–86.7 31.9–40.3 25.7–86.5 49.2–51.6 33.9–38.8 23.1–29.5 12.2–22.0 13.7–74.6 27.3–53.8 37.6–46.3 10.0–67.2 27.2–44.8 11.2–72.7 10.3–68.1 34.8–91.1 with Hb<110 g/L

8.7 6.4 Proportion of the population 9.1 29.5 78.0 17.0 76.1 24.1 50.5 50.9 29.9 84.6 36.0 50.4 26.2 16.5 39.8 41.9 35.5 23.8 83.2 11.3 18.9 23.4 81.3 14.0 51.7 21.6 12.9 22.2 59.8 30.2 36.3 22.7 12.7 40.6 26.5 22.9 32.2 32.3 36.7 33.1 70.1 Estimate ooled data from one regional and Notes one state level survey one state level 5242 mended cut-off groups: 1.00–1.99 and 4.92–4.99 yrs groups:

c 50 pooled age by d ata disaggregated 48 pooled age by d ata disaggregated 820 from < 1 to >2 y of age ranges a ge 164 calculated from 2 age p revalence 2441 1083 a djusted for altitude 4466 a djusted for altitude 5204 4640 4972 a djusted for altitude 3097 1443 5359 a djusted for altitude 2962 3327 calculated for recom- p revalence 2558 pooled age by d ata disaggregated 3226 pooled age by d ata disaggregated 1553, 1553, p Reference

n o estimate possible

Size 369 494 443 100 969 224 4.99 Sample 3900 2287 3597 5015 7015 1749 1970 1010 1449 12788 Survey Information

0.50 Age range 0.50–4.99 0.50–4.99 0.50–4.99 0.50–4.99 0.50–4.99 0.00–4.99 0.50–4.99 0.50–4.99 0.50–6.99 1.00–4.99 0.00–6.99 0.00–4.99 0.50–4.99

survey Level of

2000 n 1993 n 1994 n 1995 n 2001 n 2001 n 1999 n 2004 n ns –4.99 2003 n 1995 n ns – NS 1995 n 1996 n 1999 n (years) Date of survey 1997–1998 n 2002–2003 n 2004–2005 n s ee note 1994, 1995 1994, f

1 R

a 81 R 20 R 43 R 28 R 490 R 839 162 R 120 R 186 160 R 5679 R 4063 R 4380 R 5600 5401 R 1966 R 8496 4643 R 2612 3288 6001 R 6301 R 4195 R 9230 (000) General 10497 27678 16367 R 14426 R 47594 43379 R 20912 36992 28380 84477 38499 R 10545 R 47983 21629 25193 R 11936 R 134375 161209 142537 R

6 0 2 4 1 Population 2006 Population 86 72 69 15 12 25 23 603 962 985 273 208 734 253 280 303 344 810 836 559 206 (000) 3646 2925 1518 5183 2262 1622 5252 2996 9839 1804 2335 1046 7384 1532 3225 1870 0–4.99y 22548 21339

d Country estimates of anaemia prevalence in preschool-age children incent and the Grenadines A frica A rabia V ome and P rincipe T akistan alau anama ew Guinea apua N ew araguay eru oland ortugal N epal S eychelles N etherlands S ierra L eone ew Zealand N ew S ingapore N icaragua S lovakia N iger S lovenia N igeria S olomon Islands N iue S omalia N orway S outh O man S pain P S ri L anka P S udan P

P P P P hilippines P P Qatar R epublic of Korea

R epublic of M oldova R omania

R ussian F ederation R wanda S aint Kitts and N evis S aint L ucia S aint S amoa S an M arino S ao S audi S enegal S erbia and M ontenegro

A3.1 Table Member State

Annex 3 23 24 Table A3.1 Country estimates of anaemia prevalence in preschool-age children Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<110 g/L (number of individuals)(000) 0–4.99y General Date of survey Level of Sample Public health (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Suriname 45 452 R 25.7 7.3–60.3 12 3–27 moderate Swaziland 134 1029 R 46.7 15.6–80.6 63 21–108 severe Sweden 492 9070 R 8.6 1.9–30.7 42 10–151 mild Switzerland 346 7264 R 6.3 1.3–26.1 22 4–90 mild Syrian Arab Republic 2563 19512 R 41.0 13.9–74.9 1050 357–1918 severe Tajikistan 831 6591 2003 n 0.50–4.99 1910 4182 adjusted for altitude 37.7 34.7–40.8 313 288–339 moderate Thailand 4992 64762 1995 n 0.00–5.99 3260 3961 25.2 23.2–27.4 1258 1156–1366 moderate The Former Yugoslav Republic 116 2037 1999 n 0.50–4.99 1079 1609 25.8 22.3–29.7 30 26–34 moderate of Macedonia Timor Leste 198 1007 2003 n 0.00–4.99 5029 5050 adjusted for altitude 31.5 29.7–33.3 62 59–66 moderate Togo 1030 6306 R 52.4 19.6–83.3 540 202–858 severe Tonga 12 103 R 27.6 8.1–62.3 3 1–7 moderate Trinidad and Tobago 91 1309 R 30.4 9.1–65.5 28 8–59 moderate Tunisia 808 10210 1996–1997 n 0.00–5.99 965 2485 21.7 18.2–25.6 175 148–207 moderate Turkey 7195 74175 R 32.6 10.1–67.4 2344 728–4853 moderate Turkmenistan 491 4899 2000 n 0.00–4.99 2950 3209 35.8 33.4–38.3 176 164–188 moderate Tuvalu 1 10 R 34.2 10.6–69.4 0 0–1 moderate Uganda 6210 29857 2000–2001 n 0.50–4.99 5833 3207 64.1 62.3–65.8 3981 3871–4087 severe Ukraine 1922 45986 2002 n 0.50–3.07 896 5172 22.2 18.6–26.3 427 357–505 moderate United Arab Emirates 346 4657 R 27.7 8.0–62.9 96 28–218 moderate United Kingdom of Great Britain 3339 59847 1992–1993 n 1.50–4.57 951 3279 8.0 5.9–10.8 267 196–361 mild and Northern Ireland United Republic of Tanzania 6079 39025 2004–2005 n 0.50–4.99 7300 5221 adjusted for altitude. 71.8 70.3–73.2 4365 4275–4452 severe United States of America 20568 301029 1999–2002 n 1.00–4.99 1357 4738 3.1 2.0–4.7 638 418–968 no public health problem Uruguay 281 3487 R 19.1 5.0–51.3 54 14–144 mild Uzbekistan 2861 26980 2002 n 0.50–4.99 2305 4950 data disaggregated by age, 38.1 35.3–40.9 1090 1011–1171 moderate prevalence calculated for recommended cut-off for age group 3–4 years, adjusted for altitude. Vanuatu 30 215 R 59.0 24.9–86.2 18 7–26 severe worldw Venezuela 2877 27216 R 33.1 10.3–68.1 953 297–1958 moderate Vietnam 8002 85344 2000–2001 n 0.00–4.99 7024 3408 34.1 32.6–35.7 2729 2605–2855 moderate Yemen 3762 21639 R 68.3 33.0–90.5 2571 1240–3403 severe

i Zambia 2033 11861 2003 n 0.50–4.99 729 5098 52.9 47.8–58.0 1075 971–1179 severe de prevalence of anaem of prevalence de Zimbabwe 1750 13085 1999 n 1.00–5.99 327 2641 19.3 14.0–26.1 338 244–456 mild a population figures are based on the 2006 projection from the 2004 revision from the United Nations Population Division. b level of survey: N=nationally representative, F=2+ surveys at the first administrative level boundary, R=regression-based estimate. c corresponds to the numerical reference available in the WHO Global Database on Anaemia (http://www.who.int/vmnis/en/). d on 3 June 2006, the Permanent Representative of the Republic of Serbia to the United Nations and other International Organizations in Geneva informed the Acting Director-General of the WHO that “the membership of the state union Serbia and Montenegro in the United Nations, including all organs and the organizations of the United Nations system, is continued by the Republic of Serbia on the basis of Article 60 of the Constitutional Charter of Serbia and Montenegro, activated by the Declaration of Independ- ence adopted by the National Assembly of Montenegro on 3 June 2006”. Estimates used or referred to in this document cover a period of time preceding that communication. i a 1993–2005 problem Public health 0–0 m ild 0–1 m oderate 2–8 m ild 0–3 m oderate 1–7 m oderate 0–2 m oderate 3–4 s evere 3–4 m oderate 0–0 m oderate

6–35 m oderate 3–33 m ild 7–53 m oderate 3–45 m ild 4–24 m oderate 2–24 m oderate 6–40 m oderate 2–11 s evere 7–23 s evere 4–25 m oderate 7–106 m ild 40–70 m oderate 13–53 s evere 8–134 m ild 71–94 s evere 12–36 m oderate 18–93 m oderate 56–396 m oderate 79–116 m oderate 24–151 m oderate 46–157 s evere 95% CI 118–525 m oderate 206–680 s evere 241–288 s evere 405–486 s evere 143–230 s evere 252–332 s evere 253–320 s evere 143–435 s evere 103–606 m oderate 162–553 s evere 451–1345 s evere 363–2248 m oderate 1286–2263 s evere 4693–5478 m oderate 0 1 4 1 3 1 4 9 3 6 0 18 32 11 54

24 14 33 97 13 19 38 83 71 16 22 12 51 Population with anaemia Population 956 305 463 177 266 448 186 295 286 307 299 105 369 1767 1077 5076 (number of individuals)(000) Estimate

95% CI 4.1–44.0 8.1–56.9 6.6–20.8 2.7–41.6 3.8–45.6 7.2–54.2 9.1–59.4 7.0–54.1 8.2–57.6 3.0–41.7 5.6–55.1 9.8–60.8 2.4–40.9 9.4–60.1 8.9–58.8 9.5–60.2 28.8–85.9 12.0–66.1 16.6–73.8 25.4–83.9 10.0–61.3 28.3–49.6 34.2–60.2 49.7–53.7 65.8–78.7 20.3–79.2 30.2–44.3 12.4–66.9 34.3–43.7 10.0–61.5 61.9–74.1 36.2–58.2 56.8–74.8 44.9–56.8 15.7–72.6 47.2–62.2 28.1–85.6 26.7–31.2 10.7–63.0 24.3–82.3 24.2–82.7 15.5–45.0 24.2–82.5 14.0–71.6 with Hb<110 g/L

Proportion of the population 34.0 15.5 29.5 12.0 15.5 38.4 23.3 47.0 25.8 51.7 72.7 49.6 37.0 34.8 29.1 38.9 29.7 68.3 47.1 66.4 50.9 41.3 54.8 60.4 28.9 55.0 27.2 27.9 55.1 39.1 61.0 42.8 57.1 25.4 12.4 27.7 23.0 12.9 21.3 11.5 28.3 31.1 55.3 28.4 Estimate

Notes gestation 1–3, 1–3, ( H b <110 g/ L gestation age 4 mo, <105 g/ L <106 g/ L 4 mo, 7 mo, 6 mo, <114 g/ L <107 g/ L 6 mo, 5 mo, 8 mo, <119 g/ L 9 mo) 8 mo,

c 3208 a djusted for altitude. 4682 d ifferent H b cut-off for gestational 3256 n ational survey in rural areas 1062 3461 a djusted for altitude 5095 3328 4948 5782 3206 5214 a djusted for altitude 1722 5287 1634 a djusted for altitude. Reference

68 Size 169 157 108 364 357 817 441 153 209 535 330 Sample 4661 3160 Survey Information

Age range 13.00– NS 15.00–49.99 15.00–44.99 16.00–45.99 15.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99

survey Level of R R R R

R R R R R R R R R R R R 2000 n 2001 n 2001 n 2001 n 1995 n 2003 n 2003 n ns – NS 2000 n 2004 n 1999 n 2002 n ns – NS 1996 n ns – NS (years) Date of survey 1994–1995 n ns – NS 2003–2004 n

a 67 82 18 327 739 R 270 R 275 382 519 819 3147 3007 8205 8471 9700 8703 2211 9354 3912 1760 R 7671 7834 4093 4117 R 4399 4556 R (000) General 31082 R 33354 R 16400 R 39134 R 20366 R 10437 R 13634 14351 16601 32566 R 10032 16465 R 46279 R 18454 11294 144437 188883

1331217

1 2 6 3 7 8 0 Population 2006 Population 54 37 72 12 92 66 36 44 64 16 28 80 41 PW 712 811 696 254 141 108 366 263 655 395 444 562 327 151 508 251 962 190 670 129 (000) 1567 3759 3697 17566 Country estimates of anaemia prevalence in pregnant women aso A frican R epublic erde V ustralia ustria A fghanistan A lbania lgeria A lgeria A ndorra A ngola A ntigua and Barbuda A rgentina A rmenia A A A zerbaijan

Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bhutan Bolivia Bosnia and H erzegovina Botswana Brazil Brunei D arussalam Bulgaria Burkina F Burundi C ambodia C ameroon C anada C ape C entral C had C hile C hina C olombia C omoros C ongo C ook Islands C osta R ica C ote d’Ivoire C roatia C uba

Table A3.2 Table Member State

Annex 3 25 26 Table A3.2 Country estimates of anaemia prevalence in pregnant women Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<110 g/L (number of individuals)(000) PW General Date of survey Level of Sample Public health (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Cyprus 10 845 R 25.2 8.0–56.5 3 1–6 moderate Czech Republic 91 10209 R 22.3 6.9–52.9 20 6–48 moderate Democratic People’s Republic 326 22583 1998 n ns–NS 72 3090 survey covers 71% of population, 34.7 21.1–51.3 113 69–167 moderate of Korea exclusion of counties due to accessibility Democratic Republic of Congo 3094 59320 2005 n ns–NS 949 5764 67.3 63.0–71.4 2082 1948–2208 severe Denmark 60 5446 R 12.4 2.8–41.0 7 2–25 mild Djibouti 27 807 R 56.2 25.3–83.0 15 7–23 severe Dominica 2 80 1996–1997 n ns–NS 148 3758 35.1 25.1–46.6 1 0–1 moderate Dominican Republic 211 9021 R 39.9 14.6–72.1 84 31–152 moderate Ecuador 292 13419 R 37.8 13.9–69.6 110 41–203 moderate Egypt 1939 75437 2000 n 15.00–49.99 602 1940 45.4 39.9–51.1 880 773–990 severe El Salvador 165 6999 1998 n 15.00–49.99 451 3107 data disaggregated by trimester 10.5 7.1–15.2 17 12–25 moderate pooled, prevalence calculated for recommended cut-off from non-WHO cut-off, adjusted for altitude. Equatorial Guinea 23 515 R 41.7 13.6–76.5 10 3–18 severe Eritrea 180 4560 R 55.3 24.2–82.7 100 44–149 severe Estonia 14 1325 R 22.7 6.9–53.8 3 1–7 moderate Ethiopia 3201 79289 R 62.7 30.1–86.7 2006 965–2776 severe Fiji 19 854 1993 n 15.00–NS 54 2699 55.6 37.0–72.8 10 7–14 severe Finland 55 5262 R 15.0 3.9–43.3 8 2–24 moderate France 731 60723 R 11.5 2.5–39.6 84 18–290 mild Gabon 41 1406 R 46.2 17.0–78.3 19 7–32 severe Gambia 52 1556 1999 n 15.00–49.99 401 2806 75.1 68.7–80.6 39 36–42 severe Georgia 47 4434 R 41.6 15.7–73.1 19 7–34 severe Germany 671 82716 R 12.3 2.6–42.2 83 18–283 mild Ghana 688 22556 2003 n 15.00–49.99 400 4943 64.9 58.0–71.2 447 400–490 severe Greece 100 11140 R 18.6 5.1–49.2 19 5–49 moderate worldw Grenada 6 104 R 31.4 10.8–63.2 2 1–4 moderate Guatemala 447 12911 2002 n 15.00–49.99 541 4586 hb <110 g/L for 1–3 months 22.1 17.6–27.4 99 78–122 moderate gestational age, Hb <106, 105, 107, 110, 114, 119 g/L for 4, 5, i de prevalence of anaem of prevalence de 6, 7, 8, 9 months of gestational age respectively, adjusted for altitude. Guinea 396 9603 2000 n ns–49.99 291 2780 63.2 55.1–70.6 250 218–280 severe Guinea-Bissau 85 1634 R 57.7 25.9–84.2 49 22–71 severe Guyana 14 752 1996–1997 n ns–NS 269 3094 52.0 43.6–60.3 7 6–9 severe Haiti 257 8650 2000 n 15.00–49.99 381 3264 adjusted for altitude. 63.2 56.1–69.7 162 144–179 severe Honduras 209 7362 1996 n ns–NS 105 3095 32.4 21.2–46.1 68 44–96 moderate Hungary 92 10071 R 20.7 6.2–50.6 19 6–46 moderate Iceland 4 297 R 11.8 2.5–40.8 0 0–2 mild i

a 1993–2005 India 25753 1119538 1998–1999, 2000 n, F 15.00–49.99 5718 2972, data pooled from national survey 49.7 47.9–51.5 12799 12328–13271 severe 3780a and state survey excluded from national survey and completed later, adjustment for altitude, smoking. Indonesia 4399 225465 R 44.3 17.3–75.2 1950 761–3308 severe Iran (Islamic Republic of) 1447 70324 1994-1995 n 15.00–49.99 79 3015 adjusted for altitude. 40.5 26.5–56.2 586 384–814 severe problem Public health 0–2 m oderate 0–2 m ild 4–7 s evere 0–2 m oderate 0–1 m oderate 6–8 m oderate 0–2 m oderate 0–0 m ild 0–0 m ild

2–30 m ild 6–64 m ild 6–34 m oderate 2–12 m oderate 7–42 m oderate 8–17 m oderate 2–17 m oderate 8–40 m oderate 6–35 m oderate 5–73 m oderate 3–26 m oderate 18–24 s evere 48–70 m oderate 14–77 m oderate 17–93 m oderate 36–69 m oderate 20–232 m ild 43–500 m ild 19–138 m oderate 52–173 s evere 91–124 s evere 30–105 s evere 95% CI 138–692 m oderate 695–896 s evere 301–433 s evere 227–310 s evere 205–208 m oderate 473–547 s evere 459–652 m oderate 226–315 m oderate 173–632 s evere 196–738 s evere 541–634 s evere 257–701 s evere 3235–4033 s evere 1 5 7 1 6 1 1 7 1 0 0 9 10 23 80 21 58 62

17 40 21 12 48 69 21 17 22 51 Population with anaemia Population 377 170 797 117 109 367 268 207 513 550 269 409 465 591 520 3656 (number of individuals)(000) Estimate

95% CI 3.6–45.1 4.7–47.4 3.9–45.1 3.8–43.6 8.2–58.1 7.9–56.4 7.5–55.5 2.0–38.8 8.4–57.7 0.9–34.7 5.4–50.0 2.9–41.0 4.8–47.7 14.0–70.1 35.0–46.7 31.6–46.3 48.1–61.9 14.2–70.1 10.7–63.5 12.0–66.3 24.9–83.4 10.9–63.5 17.3–35.6 52.2–71.1 12.2–66.7 41.0–59.1 40.0–54.7 38.0–38.6 39.4–70.4 67.7–78.4 13.9–70.1 22.8–80.7 32.5–42.8 21.9–31.1 14.0–69.4 13.6–69.1 31.2–43.6 22.2–81.0 20.8–78.6 10.0–63.6 68.3–80.0 23.2–44.3 32.3–88.3 59.0–73.6 with Hb<110 g/L

6.3 Proportion of the population 14.8 15.5 40.7 14.8 38.7 26.0 55.1 38.4 34.1 25.0 31.6 25.4 62.1 34.5 10.3 50.1 47.3 55.4 73.4 26.1 52.7 37.5 26.2 37.2 49.6 19.2 74.6 12.5 32.9 66.7 38.2 17.4 31.3 56.4 24.2 38.3 38.1 37.8 37.3 52.4 30.6 17.6 65.5 Estimate

Notes surveys carried out in same year. surveys carried out in same year. size, 20. size, and smoking.

c national d ata pooled from two 50 395 d ata pooled from the Islands of 3759 3442 a djusted for altitude 5356 adjusted for altitude p revalence 1242 5190 a djusted for altitude and smoking. 5201 a djusted for altitude and smoking. 5795 2987 3446 2997 a djusted for altitude. 3469 1083 a djusted for altitude. 3109 3389, 4382 Reference

a djusted for altitude (3389 only).

m auritius and R odrigues

but small sample n ational data,

74 Size 541 336 390 172 199 229 352 524 664 697 462 418 149 318 Sample Survey Information

Age range 15.00– NS 13.00–46.99 15.00–49.99 15.00–49.99 14.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99 12.00–49.99 15.00–44.99 15.00–45.99

survey Level of R R R

R R R R

R R R R 1999 n 2002 n 1999 n ns –50.99 2004 n 1999 n 2004 n 2004 n ns – 224958 2001 n 2001 n 1995 n ns – NS 2000 n 2000 n 1993 n (years) Date of survey 2003–2004 n 1998–1999 n 1997–1998 n ns – NS

a 64 R 36 14 101 471 337 403 111 R 4210 6847 R 2662 5837 2765 R 5325 6058 R 2295 3614 R 1791 3356 5968 3417 R 3158 1256 2679 R 2052 R 4063 R 5600 (000) General 29551 R 58140 14812 35106 19105 13166 25796 13918 31943 20158 R 51009 27678 16367 14426 R 128219 108327 134375

2 6 4 1 3 0 0 Population 2006 Population 66 51 54 21 66 49 31 10 20 57 55 54 PW 987 134 516 151 238 116 208 175 140 732 567 540 698 131 723 781 938 793 178 155 793 (000) 1146 1447 2099 5481 Country estimates of anaemia prevalence in pregnant women rab Jamahiriya A rab Jamahiriya eople’s D emocratic R epublic eople’s Iraq Ireland Israel Italy Jamaica Japan Jordan

Kazakhstan Kenya Kiribati Kuwait Kyrgyzstan L ao P L atvia L ebanon

L esotho

L iberia ibyan L ibyan L ithuania L uxembourg M adagascar M alawi M alaysia M aldives M ali M alta M arshall Islands M auritania M auritius

M exico M icronesia ( F ederated S tates of) M onaco M ongolia M orocco M ozambique M yanmar N amibia N auru N epal N etherlands ew Zealand N ew N icaragua N iger N igeria

Table A3.2 Table Member State

Annex 3 27 28 Table A3.2 Country estimates of anaemia prevalence in pregnant women Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<110 g/L (number of individuals)(000) PW General Date of survey Level of Sample Public health (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Niue 0 1 R 31.7 10.7–64.2 0 0–0 moderate Norway 54 4643 R 9.3 1.7–38.4 5 1–21 mild Oman 66 2612 2000 n 15.00–49.99 375 4218 42.7 35.8–49.9 28 24–33 severe Pakistan 4890 161209 2001 n ns–NS 179 4640 39.1 29.6–49.5 1912 1446–2422 moderate Palau 0 20 R 27.3 9.0–58.7 0 0–0 moderate Panama 70 3288 1999 n ns–NS 143 3097 36.4 26.1–48.1 26 18–34 moderate Papua New Guinea 172 6001 R 55.2 24.2–82.6 95 42–142 severe Paraguay 181 6301 R 39.3 14.6–71.1 71 26–129 moderate Peru 632 28380 2004 n 15.00–49.99 962 5359 adjusted for altitude. 42.7 38.4–47.2 270 242–298 severe Philippines 1997 84477 2003 n ns–NS 585 5242 43.9 38.3–49.6 877 765–991 severe Poland 371 38499 R 25.3 8.1–56.5 94 30–210 moderate Portugal 109 10545 R 17.3 4.8–46.6 19 5–51 moderate Qatar 15 839 R 29.1 9.7–61.2 4 1–9 moderate Republic of Korea 447 47983 R 22.6 7.0–53.2 101 31–238 moderate Republic of Moldova 44 4195 R 36.5 13.2–68.4 16 6–30 moderate Romania 206 21629 R 30.0 10.2–61.9 62 21–128 moderate Russian Federation 1580 142537 R 20.8 6.0–51.8 329 95–818 moderate Rwanda 393 9230 1996 n ns–NS 161 2558 10.6 5.5–19.4 42 22–76 mild Saint Kitts and Nevis 1 43 R 25.6 8.3–56.9 0 0–1 moderate Saint Lucia 3 162 R 33.4 11.7–65.5 1 0–2 moderate Saint Vincent and the Grenadines 2 120 R 32.7 11.4–64.7 1 0–2 moderate Samoa 5 186 R national data, but small sample 33.4 11.7–65.4 2 1–3 moderate size, 20. San Marino 0 28 R 11.3 2.2–41.5 0 0–0 mild Sao Tome and Principe 5 160 R 40.4 15.3–71.8 2 1–4 severe Saudi Arabia 684 25193 R 32.0 11.1–63.9 219 76–437 moderate Senegal 432 11936 R 57.6 26.1–83.9 249 113–363 severe Serbia and Montenegrod 118 10497 R 33.6 11.8–65.8 40 14–78 moderate Seychelles 4 81 R 24.9 7.9–56.1 1 0–2 moderate Sierra Leone 268 5679 R 59.7 27.1–85.5 160 73–229 severe worldw Singapore 38 4380 R 23.8 7.4–55.1 9 3–21 moderate Slovakia 51 5401 R 25.2 8.1–56.3 13 4–29 moderate Slovenia 17 1966 R 18.9 5.4–48.8 3 1–8 mild

i Solomon Islands 15 490 R 51.1 21.6–79.9 8 3–12 severe de prevalence of anaem of prevalence de Somalia 382 8496 no estimate possible South Africa 1048 47594 R 21.8 6.3–53.8 229 66–563 moderate Spain 463 43379 R 17.6 4.9–46.9 82 23–217 mild Sri Lanka 324 20912 2001 n ns–NS 1696 4972 adjusted for altitude. 29.3 26.3–32.5 95 85–105 moderate Sudan 1167 36992 R 57.7 26.0–84.1 674 304–982 severe Suriname 9 452 R 32.4 10.9–65.1 3 1–6 moderate Swaziland 29 1029 R 24.3 6.6–59.2 7 2–17 moderate Sweden 97 9070 R 12.9 3.0–41.6 13 3–40 mild Switzerland 65 7264 1999 n 16.00–42.99 381 3402 prevalence calculated from mean 9.7 6.2–14.8 6 4–10 mild and SD i a 1993–2005 Syrian Arab Republic 545 19512 R 39.3 14.6–71.0 214 80–387 moderate Tajikistan 186 6591 R 44.6 17.7–75.2 83 33–140 severe Thailand 993 64762 1995 n ns–NS 242 3961 22.3 15.8–30.6 221 157–304 moderate The Former Yugoslav Republic of Macedonia 23 2037 R 31.8 11.0–63.8 7 3–15 moderate - ontenegro problem M Public health erbiaand eclarationIndependof S D 0–2 m oderate 0–0 m oderate 3–4 s evere

2–12 m oderate 7–44 m oderate 5–33 m oderate 10–16 m oderate 32–83 m oderate 11–68 m oderate 51–191 s evere 34–235 m oderate 25–292 m oderate 86–430 m oderate 39–123 m oderate 95% CI 592–742 s evere 763–881 s evere 152–377 m ild 250–418 s evere 489–570 m oderate 238–753 s evere 162–292 s evere 221–1073 s evere 1 6 0 4 13 54 33

21 15 72 Population with anaemia Population 121 597 666 108 100 823 241 335 237 529 520 226 (number of individuals)(000) Estimate ontenegro,activated theby M

3.6–8.9 95% CI 8.7–59.6 9.2–59.6 3.8–44.7 8.8–58.7 18.3–28.2 21.1–79.2 12.0–66.1 10.0–61.7 19.0–49.2 14.8–72.2 10.0–62.2 11.4–65.5 36.6–45.9 54.0–62.3 40.0–67.0 48.2–65.9 14.4–71.9 29.8–34.7 26.6–84.1 33.6–60.6 10.2–32.0 erbiaand S WHOthat “the membership theofstate union with Hb<110 g/L

harterof 5.7 C Proportion of the population 22.9 50.2 29.7 32.3 40.2 33.1 41.2 27.3 15.2 58.2 53.8 57.3 39.6 32.2 58.1 46.9 18.8 34.0 29.9 27.9 27.1 Estimate

onstitutional irector-Generaltheof C D cting A rticlethe60of A

Notes cut-off calculated from prevalence cut-off calculated from prevalence , adjusted for altitude. for 120 g/ L , mended cut-off from non- WHO cut-off.

c 5050 for recommended p revalence 2485 s mall sample size 3207 5221 a djusted for altitude and smoking. 4738 2293 calculated for recom- p revalence 3196 3408 2477 2641 erbiatheonbasis of Reference S

rganizationsGenevain informed the

70 Size 549 860 615 100 234 100 100 epublicof Sample 1075 2744 ivision. R Survey Information =regression-based estimate. opulation D

Age range 13.00– NS 15.00–49.99 19.00–40.99 15.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99 ations P

b ationsandother International nited N N

naemia (http://www.who.int/vmnis/en/). survey Level of nited U ationssystem, continuedis theby N stimates used or referred to in this document cover a period of time preceding that communication.

R R nited R R R r

R R U atabase on A 2003 n 1996 n 1996 n 1998 n ns – NS 1999 n (years) erbiatheto Date of survey 1996–1997 n 2000–2001 n 2004–2005 n 1999–2002 n 2000–2001 n ns – NS S

a epublicof 10 R 103 R 215 1007 6306 1309 4899 R 4657 R 3487 R (000) General 10210 74175 29857 45986 59847 39025 26980 27216 85344 21639 11861 13085 301029

=2+ surveys at the first administrative level boundary, R ontenegro on 3 June 2006”. E

2 0 6 Population 2006 Population 56 19 74 56 PW 242 168 109 395 654 623 598 895 482 384 (000) 1486 1616 1414 4233 1642 epresentativetheof R ssembly of M ational A ermanent P =nationally representative, F anzania T ations,including organsall andtheorganizations theof A merica N Country estimates of anaemia prevalence in pregnant women obago T nited U A rab E mirates n 3 June2006,3 then orresponds to the numerical reference available in the WHO GlobalD opulation figures are based on the 2006 projection from the 2004 revision from the U evel of survey: N in thein ence adopted by the N ietnam anuatu imor L este enezuela ogo onga rinidad and unisia urkey urkey urkmenistan uvalu l o p c T

T T T T T T T U ganda U kraine U nited U nited Kingdom of Great Britain and N orthern Ireland U nited R epublic of U nited S tates of U ruguay U zbekistan

V V V Yemen Zambia Zimbabwe

a b c d Table A3.2 Table Member State

Annex 3 29 30 Table A3.3 Country estimates of anaemia prevalence in non-pregnant women of reproductive age Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<120 g/L (number of individuals)(000) Women General Date of survey Level of Sample Public health 15.00–49.99y (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Afghanistan 6645 31082 2004 n 15.00–49.99 1142 5173 adjusted for altitude 24.7 21.3–28.4 1254 1084–1442 moderate and smoking. Albania 831 3147 R 21.1 7.5–46.8 164 58–364 moderate Algeria 9524 33354 R 31.4 12.4–59.8 2770 1090–5272 moderate Andorra 17 67 R 16.2 5.5–39.0 3 1–6 mild Angola 3764 16400 R 52.3 25.0–78.3 1544 737–2312 severe Antigua and Barbuda 22 82 R 26.5 9.9–54.0 5 2–11 moderate Argentina 9828 39134 R 18.0 6.3–42.1 1647 571–3841 mild Armenia 885 3007 2000 n 15.00–49.99 5968 3208 data pooled for NPNLWd and LW, 12.4 11.3–13.6 105 96–116 mild adjusted for altitude. Australia 5114 20366 R 14.7 4.9–36.6 714 238–1780 mild Austria 1993 8205 R 14.8 5.0–36.5 283 95–701 mild Azerbaijan 2551 8471 2001 n 15.00–44.99 1749 4682 40.2 37.0–43.5 969 892–1048 severe Bahamas 91 327 R 22.7 8.3–48.9 19 7–42 moderate Bahrain 185 739 2002 n 14.00–49.99 384 5391 51.3 44.3–58.3 88 76–100 severe Bangladesh 37148 144437 2001 n 15.00–45.99 1195 3256 national survey in rural areas; 33.2 29.5–37.1 11085 9863–12379 moderate data pooled for NPNLW, LW adolescents. Barbados 76 270 R 17.2 5.9–40.6 13 4–30 mild Belarus 2643 9700 R 19.4 6.7–44.5 496 172–1136 mild Belgium 2421 10437 R 13.5 4.5–34.4 313 104–795 mild Belize 72 275 R 31.2 12.2–59.6 20 8–39 moderate Benin 1988 8703 2001 n 15.00–49.99 2762 3461 data pooled for NPNLW and LW, 63.2 60.6–65.7 1025 983–1065 severe adjusted for altitude. Bhutan 533 2211 2002 n 16.00–ns 5150 1800 subjects recruted, final 54.8 41.0–67.9 256 191– 317 severe sample size not specified, adjusted for altitude. Bolivia 2308 9354 2003-2004 n 15.00–49.99 5577 5095 data pooled for 32.9 31.2–34.7 673 638–709 moderate npnlw and LW Bosnia and Herzegovina 1001 3912 R 21.3 7.6–47.2 206 73–455 moderate Botswana 455 1760 1994 n 15.00–49.99 315 2805 32.7 25.8–40.4 135 106–166 moderate worldw Brazil 52301 188883 R 23.1 8.4–49.4 11213 4093–24033 moderate Brunei Darussalam 110 382 1996-1997 n 15.00–49.99 3334 data disaggregated by age pooled, 20.4 11.4–33.8 21 12–34 moderate prevalence calculated for recom- i de prevalence of anaem of prevalence de mended cut-off from non-WHO cut-off. Bulgaria 1872 7671 R no data available 17.7 6.0–41.9 319 108–757 mild Burkina Faso 3038 13634 2003 n 15.00–49.99 3830 4948 data pooled for NPNLW and LW 52.0 49.8–54.2 1239 1186–1292 severe Burundi 1856 7834 2003 n ns–NS 973 5782 28.0 24.2–32.2 409 354–470 moderate Cambodia 3795 14351 2000 n 15.00–49.99 3402 3206 data pooled for NPNLW and LW 57.3 54.9–59.6 1920 1841–1999 severe Cameroon 4009 16601 2004 n 15.00–49.99 4549 5214 data pooled for NPNLW and LW, 44.3 42.3–46.3 1527 1457–1598 severe adjusted for altitude. Canada 8166 32566 R 14.3 4.7–35.9 1122 372–2812 mild Cape Verde 137 519 R 32.5 12.8–61.0 39 16–74 moderate

i Central African Republic 953 4093 1999 n 15.00–49.99 2396 1722 49.8 47.0–52.6 399 376–422 severe a 1993–2005 Chad 2202 10032 R 52.4 24.9–78.6 888 422–1331 severe Chile 4422 16465 2003 n 17.00–44.99 731 5783 4.8 3.0–7.5 200 126–314 no public health problem China 365828 1331217 2002 n 15.00–49.99 52463 5287 weighted prevalence 19.9 19.4–20.4 69304 67638–71001 moderate Colombia 12541 46279 R 23.6 8.6–50.2 2729 998–5813 moderate Comoros 200 819 R 47.8 21.8–75.1 82 37–129 severe problem Public health 0–2 m oderate

2–10 m oderate 2–11 m oderate 3–25 m ild 15–95 m ild 14–61 m oderate 57–74 m oderate 63–433 m ild 56–420 m ild 35–124 s evere 19–136 m ild 58–419 m ild 46–197 m oderate 90–578 m oderate 69–214 s evere 96–122 s evere 95% CI 180–564 s evere 173–254 m ild 140–971 m ild 422–490 m oderate 223–705 s evere 173–210 s evere 128–954 m ild 485–592 m oderate 809–918 s evere 214–267 m ild 132–930 m ild 783–2721 s evere 201–1292 m ild 231–1222 m oderate 359–1827 m oderate 749–6087 m ild 1808–2241 m oderate 4906–5653 s evere 4618–5071 m oderate 1057–1394 m ild 2004–2195 s evere 1044–1127 s evere 3776–11878 s evere 133187–135802 s evere 1 5 5 42 78

35 57 65 10 Population with anaemia Population 378 211 183 570 408 168 607 931 455 469 171 111 192 260 384 537 864 143 109 239 388 1725 2019 5281 4841 7927 1215 2322 2099 1086 (number of individuals)(000) Estimate 134495

95% CI 6.1–43.1 6.0–41.3 6.9–44.3 6.9–44.5 5.8–40.2 4.8–35.6 8.7–50.4 6.0–42.1 5.2–37.4 7.9–10.4 7.8–50.3 4.0–32.3 4.9–36.4 8.8–50.9 5.6–39.7 4.7–35.6 25.2–78.8 15.6–22.8 21.5–74.8 31.1–38.5 49.0–56.5 20.9–73.9 10.3–54.7 11.3–57.2 26.3–28.9 24.9–28.8 15.8–67.4 24.7–78.2 24.9–78.4 27.9–35.9 15.1–65.3 53.3–64.7 41.1–45.1 18.3–22.3 47.2–53.6 25.3–78.9 47.3–60.3 52.3–56.5 13.1–16.4 51.5–52.5 with Hb<120 g/L

9.1 Proportion of the population 18.2 18.9 47.4 19.5 16.9 34.7 52.8 46.4 27.1 27.6 26.8 38.4 17.7 31.8 59.1 12.3 43.1 14.6 20.2 50.4 52.9 53.9 54.4 14.7 16.6 52.0 52.8 17.5 19.6 14.3 23.7 29.2 52.1 52.3 15.3 36.7 22.7 24.0 14.1 Estimate

, ,

, adjusted ,

and women and women LW ,

, adjusted for altitude. ,

. , adjusted for altitude. , Notes ive age and LW age ive 15.00–19.99 yrs. 15.00–19.99 yrs. prevalence calculated from mean prevalence and SD adjusted for altitude. and 1 state survey excluded from national survey completed later; data and LW pooled for NPNLW for altitude and smoking.

c 4524 5068 5764 1940 d ata pooled for NPW 5171 a djusted for altitude. 2699 2392 pooled, age by d ata disaggregated 2806 lw 4943 and LW d ata pooled for NPNLW 4586 npw 2780 npw 3094 pooled. age by d ata disaggregated 3264 and LW d ata pooled for NPNLW 3096 npw 3556, 3556, reproduct- d ata pooled for women 2972, 2972, d ata pooled from national survey 3780a Reference

Size 906 572 447 Sample 1253 1366 9210 3777 1039 4000 4872 3062 1887 4449 3589 74974 Survey Information

Age range 20.00 NS 15.00–49.99 15.00–49.99 15.00–44.99 35.00–49.99 15.00–49.99 15.00–49.99 15.00–49.99 15.00–50.99 15.00–49.99 15.00–49.99 15.00–49.99

survey Level of R

R R R R R

R R

R R R

1996 n ns – NS 2004 n 2005 n ns – NS 2000 n 1993 n 1994 n 1999 n 2003 n 2002 n 2000 n ns –49.99 2000 n 2001 n 2000 (years) Date of survey 2002–2003 n 1996–1997 n 1998–1999, 1998–1999, F n ,

a 18 80 R 845 R 807 515 854 104 R 752 297 R 4117 R 4399 4556 R 5446 R 9021 6999 4560 R 1325 5262 R 1406 R 1556 4434 R 9603 1634 8650 7362 (000) General 18454 11294 10209 22583 59320 13419 R 75437 79289 R 60723 82716 22556 11140 12911 10071

1119538

4 Population 2006 Population 21 28 74 906 224 195 114 337 224 343 377 356 217 1195 4307 1090 3046 2503 6145 1239 2447 3486 1865 1081 1174 1194 5558 2723 3103 2110 2252 1838 2433 Women 13096 19480 18358 14086 19505 284397 15.00–49.99y (000) Country estimates of anaemia prevalence in non-pregnant women of reproductive age eople’s R epublic eople’s iji inland C ongo C ook Islands C osta R ica

C ote d’Ivoire C roatia C uba C yprus C zech R epublic D emocratic P of Korea D emocratic R epublic of C ongo D enmark D jibouti D ominica D ominican R epublic E cuador E gypt

E l S alvador E quatorial Guinea E ritrea E stonia E thiopia F F rance F

Gabon Gambia Georgia Germany Ghana Greece Grenada Guatemala Guinea Guinea-Bissau Guyana H aiti

H onduras H ungary Iceland India

Table A3.3 Table Member State

Annex 3 31 32 Table A3.3 Country estimates of anaemia prevalence in non-pregnant women of reproductive age Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<120 g/L (number of individuals)(000) Women General Date of survey Level of Sample Public health 15.00–49.99y (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Indonesia 62530 225465 R 1 study at state level and 3 local 33.1 13.1–61.8 19240 7638–35925 moderate studies Iran (Islamic Republic of) 20354 70324 1994–1995 n 15.00–49.99 1351 3015 npw, adjusted for altitude. 33.0 29.6–36.6 6239 5588–6926 moderate Iraq 7263 29551 R 45.3 19.8–73.5 2842 1245–4610 severe Ireland 1117 4210 R 17.5 6.0–41.2 183 63–433 mild Israel 1650 6847 R 18.6 6.3–43.6 282 96–661 mild Italy 13479 58140 R 14.4 4.8–35.9 1868 625–4654 mild Jamaica 709 2662 R 23.8 8.8–50.5 157 58–332 moderate Japan 28009 128219 2002 n 20.00–49.99 1164 5177a data disaggregated by age pooled. 21.3 18.2–24.8 5722 4879–6665 moderate Jordan 1474 5837 2002 n 15.00–49.99 2925 3389, 4382 data pooled for NPNLW, LW and 28.6 26.3–31.0 378 349–410 moderate npw from 2 national surveys from the same year. Adjusted for altitude (3389 only). Kazakhstan 4243 14812 1999 n 15.00–49.99 2269 2675 sample includes PW 35.5 32.8–38.3 1422 1312–1535 moderate Kenya 8454 35106 1999 n ns–50.99 2735 3442 prevalence calculated for recom- 46.4 43.8–49.0 3251 3067–3437 severe mended cut-off from mean and SD, adjusted for altitude. Kiribati 26 101 R 30.7 11.9–59.1 7 3–14 moderate Kuwait 690 2765 1998–2002 n 15.00–50.99 2993 4375 data disaggregated by age pooled, 28.7 26.5–31.0 183 168–197 moderate prevalence calculated from mean (15.00–18.99 years) Kyrgyzstan 1456 5325 1997 n 15.00–49.99 3767 2295 sample includes PW, adjusted 38.0 35.8–40.2 509 480–539 moderate for altitude. Lao People’s Democratic Republic 1480 6058 R 46.1 20.7–73.7 587 263–938 severe Latvia 587 2295 R 18.9 6.4–44.0 107 36–249 mild Lebanon 985 3614 1997–1998 n 15.00–49.99 539 3221 data pooled for NPNLW and LW, 25.2 20.4–30.7 232 187–282 moderate adjusted for altitude and smoking. Lesotho 474 1791 2004 n 15.00–49.99 2532 5356 data pooled for NPNLW and LW, 27.3 24.9–29.8 116 106–127 moderate prevalence adjusted for altitude and smoking.

worldw Liberia 748 3356 1999 n 14.00–49.99 1376 1242 58.0 54.3–61.6 333 311–353 severe Libyan Arab Jamahiriya 1647 5968 R 29.9 11.5–58.5 451 173–881 moderate Lithuania 893 3417 R 17.9 6.1–42.1 154 53–363 mild Luxembourg 118 471 R 18.8 6.5–43.3 21 7–49 mild i de prevalence of anaem of prevalence de Madagascar 4442 19105 2003–2004 n 15.00–49.99 2383 5190 data pooled for NPNLW and LW, adjusted for altitude and smoking. 45.6 42.8–48.4 1691 1587–1797 severe Malawi 2883 13166 2004–2005 n 15.00–49.99 2268 5201 data pooled for NPW and LW, adjusted for altitude and smoking. 43.9 41.0–46.8 1017 950–1084 severe Malaysia 6670 25796 R 30.1 11.5–58.7 1844 708–3596 moderate Maldives 82 337 2001 n 15.00–49.99 1287 2987 49.6 45.7–53.5 35 33–38 severe Mali 3066 13918 2001 n 15.00–49.99 3264 3446 data pooled for NPNLW and LW 61.0 58.6–63.3 1444 1388–1499 severe Malta 96 403 R 15.6 5.3–38.1 14 5–35 mild Marshall Islands 17 64 R 24.1 8.7–51.4 4 1–8 moderate Mauritania 745 3158 R 50.4 23.6–76.9 310 145–473 severe i a 1993–2005 Mauritius 344 1256 1995 n 25.00–50.99 128 395 only Mauritius Island. 14.0 7.4–24.8 45 24–80 mild Mexico 30363 108327 1998–1999 n 15.00–49.99 14451 2997 data disaggregated by age pooled, 20.8 19.9–21.8 5879 5619–6148 moderate adjusted for altitude. Micronesia (Federated States of) 28 111 R 24.2 8.9–51.2 6 2–12 moderate Monaco 8 36 R 13.3 4.3–34.3 1 0–3 mild problem Public health 1–9 m oderate 0–2 m oderate 0–0 m ild 0–2 m oderate 1–5 m oderate 0–2 m ild

4–22 m oderate 3–16 m oderate 5–10 m ild 3–19 m oderate 60–157 m ild 94–610 m ild 63–283 m oderate 24–175 m ild 77–126 m ild 76–176 m ild 45–348 m ild 21–100 m oderate 97–580 m oderate 95% CI 569–734 m oderate 350–891 s evere 183–232 m ild 172–199 m oderate 293–348 s evere 248–933 s evere 136–756 m oderate 124–912 m ild 176–1316 m ild 739–1904 s evere 624–4138 m ild 872–3393 m ild 379–2461 m oderate 565–1629 s evere 673–3275 m oderate 555–1879 s evere 2403–2901 m oderate 1748–2169 s evere 5452–6509 s evere 3980–4255 s evere 2691–2834 s evere 7631–9213 s evere 8298–10962 m oderate 2605–16931 m ild 14774–16338 s evere 4 1 0 1 2 7 7 1 9 99 71 99

54 10 Population with anaemia Population 648 658 207 268 156 526 116 136 185 320 565 367 370 269 2646 1958 5976 4120 1398 9574 2762 8412 1792 1788 1085 7448 1153 1727 1206 (number of individuals)(000) Estimate 15568

95% CI 8.3–21.5 7.6–46.8 6.8–44.2 5.1–37.1 9.5–53.3 4.8–35.6 7.9–13.0 5.8–13.6 3.6–32.6 4.4–34.0 7.5–46.8 9.7–54.0 6.5–43.1 5.0–36.9 6.8–26.6 8.4–50.5 7.0–45.5 6.9–45.1 7.4–46.2 9.3–52.1 8.9–50.9 5.7–39.5 9.5–54.4 23.4–30.2 29.6–35.7 33.5–85.1 43.0–53.4 16.3–20.7 41.0–48.9 14.3–63.6 64.4–68.9 32.8–84.7 58.8–65.1 31.6–36.5 24.2–31.9 36.9–43.8 18.9–71.1 39.4–41.4 38.2–46.1 13.7–67.0 29.1–83.9 13.5–27.8 12.6–61.2 22.3–75.4 with Hb<120 g/L

9.0 Proportion of the population 26.7 13.6 21.1 32.6 48.2 18.4 44.9 15.1 25.7 66.7 14.2 10.2 62.0 13.3 34.0 27.9 40.3 26.2 40.4 42.1 15.0 14.0 20.1 59.4 25.0 19.7 26.2 48.4 62.9 19.4 35.0 62.2 11.9 21.1 43.1 18.7 36.2 23.4 19.8 20.8 24.1 16.5 32.3 Estimate

, ,

. . , adjusted for altitude. , Notes prevalence calculated from mean. prevalence adolescents 15–19 years. adjusted for altitude. sample includes PW

c 50 589 760 s ample includes PW 2441 5247 a djusted for altitude. 3469 5246 npnlw 1083 npw 3192 pooled, age by d ata disaggregated 4466 a djusted for altitude. 4218 and female d ata pooled for women 4640 3097 5359 and LW d ata pooled for NPNLW 5242 o nly LW 5249 pooled; age by d ata disaggregated 3226 Reference

Size 211 707 432 240 Sample 1296 1784 2467 1200 3437 1088 1859 2766 1022 1523 1189 17058 Survey Information

Age range 15.00–49.99 15.00–49.99 15.00–49.99 18.00–69.99 15.00–44.99 15.00–44.99 15.00–45.99 15.00–49.99 15.00–49.99 15.00–49.99

survey Level of R R R R

R R R R R 2000 n 2004 n 2000 n 1998 n 2001 n 1993 n 2000 n 2001 n ns – NS 1999 n ns – NS 2004 n 2003 n ns – NS 2001 n 1999 n ns – NS (years) Date of survey 2001–2002 n ns – NS 1997–1998 n ns – NS 1996–1997 n 2002–2003 n ns – NS

1 R

a 81 14 20 R 43 R 28 R 839 R 162 120 R 186 160 2679 5679 R 4380 5401 R 2052 R 1966 4063 5600 4643 2612 3288 6001 R 6301 4195 R 9230 (000) General 10497 31943 20158 51009 27678 16367 14426 R 28380 84477 38499 R 10545 47983 21629 25193 R 11936 134375 161209 142537 R

4 0 5 7 Population 2006 Population 22 12 45 33 42 41 787 499 489 611 865 165 2545 8839 1315 4843 1160 1433 6969 3872 1022 1447 3043 1078 1483 1580 7469 9975 2580 1193 5611 2335 6031 2923 Women 14248 30591 39205 21977 13219 39140 15.00–49.99y (000)

e Country estimates of anaemia prevalence in non-pregnant women of reproductive age incent and the Grenadines A rabia V ome and P rincipe T akistan alau anama ew Guinea apua N ew araguay eru oland ortugal M ongolia S eychelles M orocco S ierra L eone M ozambique S ingapore M yanmar S lovakia N amibia S lovenia N auru N epal N etherlands ew Zealand N ew

N icaragua N iger N igeria N iue N orway O man

P P P P P P

P hilippines P P Qatar R epublic of Korea

R epublic of M oldova R omania R ussian F ederation R wanda S aint Kitts and N evis S aint L ucia S aint S amoa S an M arino S ao S audi S enegal S erbia and M ontenegro

Table A3.3 Table Member State

Annex 3 33 34 Table A3.3 Country estimates of anaemia prevalence in non-pregnant women of reproductive age Member State Population 2006a Survey Information Proportion of the population Population with anaemia with Hb<120 g/L (number of individuals)(000) Women General Date of survey Level of Sample Public health 15.00–49.99y (000) (000) (years) surveyb Age range Size Referencec Notes Estimate 95% CI Estimate 95% CI problem Solomon Islands 120 490 R 39.2 16.5–67.8 41 17–71 moderate Somalia 2000 8496 no estimate possible. South Africa 12675 47594 R 26.4 9.9–54.0 3074 1151–6282 moderate Spain 11200 43379 R 16.3 5.6–39.1 1751 598–4203 mild Sri Lanka 5665 20912 2001 n 15.00–49.99 4625 4972 adjusted for altitude. 31.6 29.7–33.5 1688 1588–1790 moderate Sudan 9083 36992 R 43.5 19.1–71.5 3443 1515–5656 severe Suriname 121 452 R 20.4 7.3–45.7 23 8–51 moderate Swaziland 263 1029 R 36.5 14.9–65.4 85 35–153 moderate Sweden 2036 9070 R 13.3 4.4–33.8 257 85–656 mild Switzerland 1759 7264 R 12.2 3.9–32.1 207 66–544 mild Syrian Arab Republic 5199 19512 R 33.4 13.3–62.1 1555 619–2891 moderate Tajikistan 1739 6591 2003 n 15.00–49.99 2042 4182 adjusted for altitude. 41.2 38.2–44.2 640 594–687 severe Thailand 18156 64762 1995 n 15.00–59.99 2953 3961 data pooled for NPNLW, LW and 17.8 15.9–19.8 3055 2735–3404 moderate women of working population. The former Yugoslav Republic 530 2037 1999 n 15.00–45.99 1018 1609 12.2 9.6–15.3 62 49–78 mild of Macedonia Timor Leste 230 1007 2003 n 15.00–49.99 3745 5050 adjusted for altitude. 31.5 29.4–33.6 55 51–59 moderate Togo 1494 6306 R 38.4 15.5–68.0 481 194–851 moderate Tonga 24 103 R 21.5 7.7–47.2 5 2–10 moderate Trinidad and Tobago 381 1309 R 24.3 8.9–51.5 88 32–187 moderate Tunisia 2939 10210 1996–1997 n 17.00–59.99 1951 2485 data pooled for women and LW. 26.3 23.6–29.2 729 655–808 moderate Turkey 20065 74175 R 26.3 9.9–53.6 4885 1841–9966 moderate Turkmenistan 1392 4899 2000 n 15.00–49.99 7714 3209 sample includes PW. 47.3 45.7–48.9 607 586–627 severe Tuvalu 3 10 R 26.3 9.8–53.9 1 0–1 moderate Uganda 6254 29857 2000–2001 n 15.00–49.99 5688 3207 data pooled for NPNLW and LW. 28.7 27.1–30.4 1331 1255–1410 moderate Ukraine 12180 45986 2002 n 15.00–44.99 859 5172 9.2 6.8–12.3 1084 802–1452 mild United Arab Emirates 922 4657 R 43.9 16.2–76.0 372 138–644 severe United Kingdom of Great Britain 14426 59847 200–2001 n 19.00–49.99 486 4154 npnlw 8.8 5.8–13.1 1212 803–1800 mild and Northern Ireland United Republic of Tanzania 9226 39025 2004–2005 n 15.00–49.99 9065 5221 data pooled for NPNLW and LW, 47.2 45.8–48.7 3687 3574–3801 severe worldw adjusted for altitude and smoking. United States of America 74273 301029 1999–2002 n 15.00–59.99 3866 4738 data disaggregated by age pooled, 6.9 5.9–8.1 4833 4099–5686 mild weighted prevalence. Uruguay 842 3487 R 16.9 5.8–40.3 133 45–317 mild i de prevalence of anaem of prevalence de Uzbekistan 7476 26980 1996 n 15.00–49.99 2293 prevalence calculated for recom- 64.8 50.8–76.7 4440 3478–5255 severe mended cut-off ; NPNLW. Vanuatu 53 215 1996 n 15.00–49.99 1685 3196 data pooled for NPNLW and LW. 54.1 50.7–57.4 25 24–27 severe Venezuela 7221 27216 R 28.3 10.8–56.3 1874 714–3727 moderate Viet Nam 24297 85344 2000–2001 n 15.00–49.99 7135 3408 24.3 22.9–25.7 5505 5193–5830 moderate Yemen 4895 21639 R 51.0 24.0–77.5 2042 961–3099 severe Zambia 2657 11861 2003 n 15.00–49.99 623 5098 29.1 24.3–34.4 633 529–748 moderate Zimbabwe 3281 13085 1999 n 15.00–49.99 2641 994 653–1400 a population figures are based on the 2006 projection from the 2004 revision from the United Nations Population Division. b

i level of survey: N=nationally representative, F=2+ surveys at the first administrative level boundary, R=regression-based estimate. a 1993–2005 c corresponds to the numerical reference available in the WHO Global Database on Anaemia (http://www.who.int/vmnis/en/). d lw = lactating women, NPNLW = non-pregnant non-lactating women, PW = pregnant women e on 3 June 2006, the Permanent Representative of the Republic of Serbia to the United Nations and other International Organizations in Geneva informed the Acting Director-General of the WHO that “the membership of the state union Serbia and Montenegro in the United Nations, including all organs and the organizations of the United Nations system, is continued by the Republic of Serbia on the basis of Article 60 of the Constitutional Charter of Serbia and Montenegro, activated by the Declaration of Independ- ence adopted by the National Assembly of Montenegro on 3 June 2006”. Estimates used or referred to in this document cover a period of time preceding that communication. A3.4 Country references Bhutan Afghanistan Royal Government of Bhutan – Ministry of Health and Ministry of Public Health of the Islamic Republic of Afgha- Education. Anemia among men, women and children in Bhu- nistan et al. Summary Report of the National Nutrition Sur- tan: How big is the problem? Bhutan, Ministry of Health vey, Afghanistan, 2004. Ministry of Public Health of the and Education, 2003. Ref 5150. Islamic Republic of Afghanistan, 2005. Ref 5173. Bolivia Angola Gutiérrez Sardán M et al. Bolivia Encuesta Nacional de De- Ministry of Health et al. Assessing vitamin A and iron de- mografía y Salud 2003 [Bolivia National Demographic and ficiency anaemia, nutritional anaemia among children aged Health Survey 2003]. La Paz, Ministerio de Salud y Depor- 0–60 months in the Republic of Angola [technical report]. tes, Instituto Nacional de Estadística, 2004. Ref 5095. Ministry of Health, 2000. Ref 2839. Botswana Antigua and Barbuda Ministry of Health Botswana et al. Micronutrient malnu- Micronutrient Working Group. Iron and vitamin A status trition in Botswana. A national survey to assess the status of in five Caribbean countries. Cajanus, 2002, 35 (1): 4–34. iodine, iron, and vitamin A. Gaborone, Ministry of Health, Ref 3758. 1996. Ref 2805.

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36 worldwide prevalence of anaemia 1993–2005 Ghana Jamaica Ghana Statistical Service (GSS) et al. Ghana Demographic WHO Pan American Health Organization et al. Micronu- and Health Survey 2003. Calverton, MD, ORC Macro, trient study report: an assessment of the vitamin A, E, beta- 2004. Ref 4943. carotene, and iron status in Jamaica. Kingston, WHO, Pan American Health Organization, Caribbean Food and Nu- Guatemala trition Institute, 1998 (PAHO/CFNI/98.J1). Ref 3093. Ministerio de Salud Publica y Asistencia Social et al. Gua- Micronutrient Working Group. Assessment of the iron sup- temala, Encuesta Nacional de Salud Materno Infantil 2002. plementation programme for pregnant women in Jamaica. Guatemala, Ministerio de Salud Publica y Asistencia So- Cajanus, 2002, 35 (1): 35–49. Ref 3759. cial, 2003. Ref 4586. Japan Guinea National Institute of Health and Nutrition. National Nu- Ministère de la Santé Publique. Enquête nationale sur l’ané- trition Survey of Japan in 2001 and 2002. Japan, National mie ferriprive en Guinée. Rapport Final: résumé. Guinee, Institute of Health and Nutrition, 2002. Ref 5177. 2001. Ref 2780. Jordan Guyana Department of Statistics et al. Jordan Population and Fa- Ministry of Health [Guyana] et al. Executive summary micro- mily Health Survey 2002. Calverton, MD, Department of nutrient study report – Guyana. An assessment of the vitamin Statistics Jordan, ORC Macro, 2003. Ref 3389. A, E, beta-carotene, iron and iodine status in the population. Georgetown, Ministry of Health, 1997. Ref 3094. Ministry of Health Jordan et al. National baseline survey on iron deficiency anemia and vitamin A deficiency. Amman, Haiti Ministry of Health, 2002. Ref 4382. Republique d’Haiti et al. Enquête Mortalité, Morbidité et Utilisation des Services EMMUS-III Haïti 2000. Republi- Kazakhstan que d’Haiti, 2001. Ref 3264. Academy of Preventive Medicine Kazakhstan et al. Ka- zakhstan Demographic and Health Survey 1999. Calverton, Honduras MD, Academy of Preventive Medicine and Macro Interna- Ministerio de Salud Pública et al. Encuesta Nacional de Mi- tional Inc, 1999. Ref 2675. cronutrientes Honduras, 1996. Tegucigalpa, Secretaria de Salud, Ministerio de Salud Pública, 1997. Ref 3095. Kenya Mwaniki DL et al. Anaemia and status of iron, vitamin A Secretaría de Salud et al. Encuesta Nacional de Salud Mascu- and zinc in Kenya. The 1999 National Survey. Nairobi, Mi- lina ENSM-2001. Tegucigalpa, Secretaría de Salud, 2002. nistry of Health, 2002. Ref 3442. Ref 3096. Kuwait India Jackson RT et al. Gender and age differences in anemia International Institute for Population Sciences et al. Na- prevalence during the lifecycle in Kuwait. Ecology of Food tional Family Health Survey (NFHS-2), 1998–1999: India. and Nutrition, 2004, 43 (1–2):61–75. Ref 4375. Mumbai, International Institute for Population Sciences, 2000. Ref 2972. Kyrgyzstan International Institute for Population Sciences et al. Na- Research Institute of Obstetrics and Pediatrics et al. Kyrgyz tional Family Health Survey (NFHS-2), India, 1998–1999, Republic Demographic and Health Survey, 1997. Calverton, Northeastern States: Arunachal Pradesh, Manipur, Megha- MD, Research Institute of Obstetrics and Pediatrics, Mi- laya, Mizoram, Nagaland and Tripura. Mumbai, Interna- nistry of Health of the Kyrgyz Republic and Macro Inter- tional Institute for Population Sciences, 2002. Ref 3780. national Inc, 1998. Ref 2295.

Iran (Islamic Republic of) Lao People’s Democratic Republic Ministry of Health and Medical Education et al. Multi- Ministry of Health, Lao People’s Democratic Republic. Re- centre study on iron deficiency anemia among 15 to 49 year old port on national health survey: health status of the People of women in the Islamic Republic of Iran. Islamic Republic of LAO PDR. Vientiane, Ministry of Health, 2001. Ref 770. Iran, Nutrition Department, Ministry of Health and Me- dical Education, 1995. Ref 3015.

Annex 3 37 Lebanon Micronesia (Federated States of) Hwalla N et al. Prevalence and selected determinant of iron Auerbach SB. Maternal-Child Health Survey: Pohnpei, Fe- deficiency anemia in women and under five children in Leba- derated States of Micronesia, 1993 [summary table]. Palikir, non. Beirut, 1998. Ref 3221. Pohnpei, US Public Health Service/Department of Health Services [Federated States of Micronesia], 1999. Ref 4942. Lesotho Socorro P et al. Results of vitamin A, anemia and blood lead Ministry of Health and Social Welfare et al. Lesotho De- survey among 2–4 year old children and reproductive-aged mographic and Health Survey 2004. Calverton, MD, ORC women in Yap proper and Kosrae State, Federated States of Macro, 2005. Ref 5356. Micronesia. Atlanta, Centers for Disease Control and Pre- Liberia vention, 2000. Ref 2548. Mulder-Sibanda M et al. National Micronutrient Survey. A Mongolia national prevalence study on vitamin A deficiency, iron de- Enkhbat S. Third National Nutrition Survey 2004 [perso- ficiency anemia, iodine deficiency. Monrovia, Ministry of nal communication]. Mongolia, Ministry of Health, 2004. Health and Social Welfare, Family Health Division, Uni- Ref 5247. ted Nations Children’s Fund, 1999. Ref 1242. Morocco Madagascar Ministère de la Santé Maroc. Enquête nationale sur la ca- Institut National de la Statistique et al. Enquête Démogra- rence en fer l’utilisation du sel iodé et la supplémentation par phique et de Santé de Madagascar 2003–2004. Calverton, la vitamine A, 2000. Morocco, 2000. Ref 3469. MD, ORC Macro, 2005. Ref 5190. Mozambique Malaysia Ministério da Saúde et al. Inquérito nacional seovre a defi- Ministry of Health Malaysia. Family Health. Sub System ciência de vitamina A, prevalência de anemia e malária em Health Management Information System, 2004. Malaysia, crianças dos 6–59 meses e respectivas mães. Maputo, Instituto Ministry of Health, 2005. Ref 5795. Nacional de Saúde, 2003. Ref 589. Malawi Myanmar National Statistical Office et al. Malawi Demographic and National Nutrition Center et al. A study on hemoglobin status Health Survey 2004. Calverton, MD, ORC Macro, 2005. and food practices of Myanmar women. Myanmar, National Ref 5201. Nutrition Center, Department of Health, 2001. Ref 5246. Maldives Nepal Ministry of Health and Welfare et al. Nutritional status and Ministry of Health Nepal et al. Nepal Micronutrient Status child feeding practices of Maldivian children – Report of the Survey 1998. Kathmandu, Ministry of Health, 1999. Ref National Nutrition Survey. Malé, 1994. Ref 831. 1083. Minister of Health, Republic of Maldives. Multiple Indica- tor Cluster Survey (MICS 2), Maldives. Malé, Ministry of New Zealand Health, 2001. Ref 2987. Russell D et al. NZ Food: NZ People: key results of the 1997 National Nutrition Survey. New Zealand, Ministry of Mali Health, 1999. Ref 3192. Cellule de Planification et de Statistique du Ministère de la Santé et al. Enquête Démographique et de Santé au Mali Nicaragua 2001. Calverton, MD, ORC Macro, 2002. Ref 3446. Ministerio de Salud. Encuesta nacional de micronutrientes (ENM 2000) [National survey of micronutrients (ENM Mauritius 2000)]. Managua, Ministerio de Salud, 2002. Ref 3109. Ministry of Health Mauritius. A survey of nutrition in Mau- Ministerio de Salud. Sistema integrado de vigilancia de inter- ritius and Rodrigues (1995). Port Louis, Ministry of Health, venciones nutricionales (SIVIN): primer informe de progreso 1995. Ref 395. 2002–2003 [Integrated system of monitoring nutrition inter- Mexico ventions (SIVIN): first progress report 2002–2003]. Mana- Instituto Nacional de Salud Publica. Encuesta Nacional de gua, Ministerio de Salud, 2004. Ref 4466. Nutrición 1999. Mexico City, Instituto Nacional de Salud Publica, 1999. Ref 2997.

38 worldwide prevalence of anaemia 1993–2005 Nigeria Rwanda Federal Ministry of Health and Social Services et al. Nige- Ministère de la Santé et al. National Nutrition Survey of Wo- ria National Micronutrient Survey, 1993. Nigeria, Federal men and Children in Rwanda in 1996 [final report]. Kigali, Ministry of Health and Social Services, 1996. Ref 50. Ministère de la Santé, 1997. Ref 2558.

Oman Samoa Al-Riyami A et al. National Health Survey, 2000. Volume II Mackerras D et al. Samoa national nutritional survey 1999, – Reproductive Health Study. Ministry of Health the Sulta- part 1: anaemia survey [technical report]. Apia, Department nate of Oman, 2000. Ref 4218. of Health, 2002. Ref 3226.

Al-Riyami A et al. Genetic Blood Disorders Survey in the Serbia and Montenegro1 Sultanate of Oman. Journal of Tropical Pediatrics, 2003, 49 Petrovic O et al. Multiple Indicator Cluster Survey II. The (Suppl 1): i1–20. Ref 5204. report for the Federal Republic of Yugoslavia. Belgrade, Pakistan UNICEF, 2000. Ref 2441. Pakistan Institute of Development Economics et al. Natio- Singapore nal Nutrition Survey 2001–2002. Islamabad, Government Department of Nutrition et al. National Nutrition Survey of Pakistan, Planning Commission, 2003. Ref 4640. 1998. Singapore, Ministry of Health, 2001. Ref 760. Panama South Africa Ministerio de Salud, et al. Encuesta nacional de vitamina A South African Vitamin A Consultation Group (SAVACG). y anemia por deficiencia de hierro [National survey of vitamin Children aged 6 to 71 months in South Africa, 1994: their A and iron deficiency anemia]. Panama City, Ministerio de anthropometric, vitamin A, iron and immunisation coverage Salud, 2000. Ref 3097. status. Johannesburg, South African Vitamin A Consulta- Peru tive Group, 1995. Ref 48. Ministerio de Salud Publica et al. Monitoreo nacional de Sri Lanka indicadores nutricionales 2004. Lima, Ministerio de Salud Piyasena C et al. Assessment of anaemia status in Sri Lanka Publica, Instituto Nacional de Salud, 2004. Ref 5359. 2001 [survey report]. Colombo, Ministry of Health, Nutri- Philippines tion and Welfare, Department of Health Services, Medical Research Institute, 2003. Ref 4972. Food and Nutrition Research Institute, Philippines. The Sixth National Survey 2003 [personal communication]. Sudan Manila, 2003. Ref 5242. Federal Ministry of Health et al. Comprehensive Nutrition Qatar Survey. Khartoum, Federal Ministry of Health, National Nutrition Department, 1997. Ref 1443. Amine EK. Nutritional assessment in Qatar; 1995 Oct 20– Nov 3 [assignment report]. Qatar, WHO Regional Office Elnour A et al. Endemic goiter with iodine sufficiency: a for the Eastern Mediterranean, 1995. Ref 820. possible role for the consumption of pearl millet in the etiology of endemic goiter. American Journal of Clinical Nutri- Republic of Korea tion, 2000, 71 (1): 59–66. Ref 1553. WHO Regional Office for the Eastern Mediterranean. 1995 National Nutrition Survey Report. Republic of Korea, Ministry of Health and Welfare, 1997. Ref 3327. Korean Ministry of Health and Welfare. National Health and Nutrition Survey, 2001. Seoul, Korean Ministry of Health and Welfare, 2005. Ref 5249. 1 On 3 June 2006, the Permanent Representative of the Republic of Ser- bia to the United Nations and other International Organizations in Geneva informed the Acting Director-General of the WHO that “the Romania membership of the state union Serbia and Montenegro in the United “Alfred Rusescu” Institute for Mother and Child Protec- Nations, including all organs and the organizations of the United Na- tions system, is continued by the Republic of Serbia on the basis of tion. Nutritional status of pregnant women, children under Article 60 of the Constitutional Charter of Serbia and Montenegro, 5 years and school children aged 6–7 years. “Alfred Rusescu” activated by the Declaration of Independence adopted by the National Assembly of Montenegro on 3 June 2006”. Estimates used or referred Institute for Mother and Child Protection, 2005. Ref 164. to in this document cover a period of time preceding that communication.

Annex 3 39 Switzerland Ruston D et al. The National Diet & Nutrition Survey: Hess SY et al. A national survey of iron and folate status in adults aged 19 to 64 years. Volume 4: nutritional status (an- pregnant women in Switzerland. International Journal for thropometry and blood analytes), blood pressure and physical Vitamin and Nutrition Research, 2001, 71 (5): 268–273. Ref activity. London, Her Majesty’s Stationery Office, 2004. 3402. Ref 4154.

Tajikistan United Republic of Tanzania Branca F et al. Micro-nutrient status survey in Tajikistan. National Bureau of Statistics (NBS) Tanzania et al. Tan- Rome, National Institute for Research on Food and Nutri- zania Demographic and Health Survey 2004–05. Dar es tion, Kazakh Academy of Nutrition, 2004. Ref 4182. Salaam, National Bureau of Statistics, ORC Macro. 2005. Ref 5221. Thailand Ministry of Public Health et al. The Fourth National Nutri- United States of America tion Survey of Thailand 1995. Bangkok, Ministry of Public Centers for Disease Control and Prevention. National Health, Department of Health, 1998. Ref 3961. Health and Nutrition Examination Survey 1999–2000, 2001–2002 [personal communication], 2002. Ref 4738. The former Yugoslav Republic of Macedonia Branca F et al. Multiple indicator cluster survey in FYR Uzbekistan Macedonia with micronutrient component. Rome, National Institute of Obstetrics and Gynecology et al. Uzbekistan Institute of Nutrition, 2000. Ref 1609. Demographic and Health Survey, 1996. Calverton, MD, Institute of Obstetrics and Gynecology, Macro Internatio- Timor-Leste nal Inc, 1997. Ref 2293. Ministry of Health Timor-Leste et al. Timor Leste 2003 Analytical and Information Center et al. Uzbekistan Health Demographic and Health Survey. Newcastle, Australia, Mi- Examination Survey 2002. Calverton, MD, Analytical and nistry of Health/University of Newcastle, 2003. Ref 5050. Information Center, State Department of Statistics, ORC Tunisia Macro, 2004. Ref 4950. Ministère de la Santé Publique et al. Rapport national: Vanuatu évaluation de l’état nutritionnel de la population tunisienne Harvey P et al. Report of the second national nutrition survey [National report: evaluation of the nutritional status of the 1996. Port Vila, Department of Health, 1998. Ref 3196. Tunisian population]. Tunis, Ministère de la Santé Publi- que, 1996. Ref 2485. Viet Nam Khoi HH et al. Report on Vietnam National anemia Sur- Turkmenistan vey, 2000. Hanoi, National Institute of Nutrition, 2001. Gurbansoltan Eje Clinical Research Center for Maternal Ref 3408. and Child Health et al. Turkmenistan Demographic and Health Survey 2000. Calverton, MD, ORC Macro, 2001. Zambia Ref 3209. Luo C et al. National baseline survey on prevalence and aetio- logy of anaemia in Zambia: a random cluster community sur- Uganda vey involving children, women and men. Lusaka, National Uganda Bureau of Statistics (UBOS) et al. Uganda Demo- Food and Nutrition Commission, 1999. Ref 2477. graphic and Health Survey 2000–2001. Calverton, MD, ORC Macro, 2001. Ref 3207. Micronutrient Operational Strategies and Technologies (MOST) et al. Report of the national survey to evaluate Ukraine the impact of vitamin A interventions in Zambia, July and Academy of Medical Science of Ukraine et al. Report of the November 2003. Zambia, Micronutrient Operational Stra- National Micronutrient Survey Ukraine. Ukraine, Academy tegies and Technologies, United States Agency for Inter- of Medical Science of Ukraine, 2004. Ref 5172. national Development (USAID) Micronutrient Program, 2003. Ref 5098. United Kingdom of Great Britain and Northern Ireland Gregory JR et al. National Diet and Nutrition Survey: chil- Zimbabwe dren aged 1½ to 4½ years. Volume 1: report of the diet and Ministry of Health and Child Welfare, Nutrition Unit. nutrition survey. London, Her Majesty’s Stationery Office, Zimbabwe National Micronutrient Survey: 1999. Harare, 1995. Ref 3279. Ministry of Health and Child Welfare, 2001. Ref 2641.

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